{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ad395281-31bd-48ff-8bed-3a296c05072a",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Hidden-Shift problem for bent functions using the classiq platform"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "450fbc3a-2837-44e7-90bc-e695a87ba220",
   "metadata": {},
   "source": [
    "Here we implement the hidden shift algorithm for the familty of boolean bent functions."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a13a1783-065a-46aa-9967-ba2d5affd33e",
   "metadata": {},
   "source": [
    "First, make sure we have all necessary packages:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "56787ea7-a18b-4e7b-b93a-bd419b9c1e66",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:46:19.695461Z",
     "iopub.status.busy": "2024-05-07T14:46:19.695002Z",
     "iopub.status.idle": "2024-05-07T14:46:22.174297Z",
     "shell.execute_reply": "2024-05-07T14:46:22.173578Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: galois in /home/runner/.cache/pypoetry/virtualenvs/backend-L_v8IreQ-py3.11/lib/python3.11/site-packages (0.3.5)\r\n",
      "Requirement already satisfied: numpy<1.25,>=1.21.0 in /home/runner/.cache/pypoetry/virtualenvs/backend-L_v8IreQ-py3.11/lib/python3.11/site-packages (from galois) (1.24.4)\r\n",
      "Requirement already satisfied: numba<0.58,>=0.55 in /home/runner/.cache/pypoetry/virtualenvs/backend-L_v8IreQ-py3.11/lib/python3.11/site-packages (from galois) (0.57.1)\r\n",
      "Requirement already satisfied: typing-extensions>=4.0.0 in /home/runner/.cache/pypoetry/virtualenvs/backend-L_v8IreQ-py3.11/lib/python3.11/site-packages (from galois) (4.11.0)\r\n",
      "Requirement already satisfied: llvmlite<0.41,>=0.40.0dev0 in /home/runner/.cache/pypoetry/virtualenvs/backend-L_v8IreQ-py3.11/lib/python3.11/site-packages (from numba<0.58,>=0.55->galois) (0.40.1)\r\n"
     ]
    }
   ],
   "source": [
    "!pip install galois"
   ]
  },
  {
   "attachments": {
    "663333d5-eb52-4150-a00d-8683e816d860.png": {
     "image/png": 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ggAACCCCAAAIIIIAAAggggEAOAjTUyQGZQyCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggQEMdrgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBHIQoKFODsgcAgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABGupwDSCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkIMADXVyQOYQCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgjQUIdrAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBHARoqJMDModAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQICGOlwDCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgjkIEBDnRyQOQQCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAjTU4RpAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCAHARrq5IDMIRBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQoKEO1wACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAjkI0FAnB2QOgQACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAADXW4BhBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQyEGAhjo5IHMIBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRoqMM1gAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBADgI01MkBmUMggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIEBDHa4BBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRyEKChTg7IHAIBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAARrqcA0ggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIJCDAA11ckDmEAgggAACxQt84xvfKD4IIkAAgZYJVCqVlu27zDvm3lfm3CN2BOoLcO9LNuLel+zCWgTaRYB7X3VOct+rNmENAu0mwL2vOke591WbsAaBdhPg3tduOcr5IICALkBDHV2DeQQQQACBthXgw3vbZi0nhoAvwAf35AuBe1+yC2sRaBcB7n3JOcm9L9mFtQi0iwD3vuqc5L5XbcIaBNpNgHtfdY5y76s2YQ0C7SbAva/dcpTzQQABXYCGOroG8wgggAACbSvAh/e2zVpODAFfgA/uyRcC975kF9Yi0C4C3PuSc5J7X7ILaxFoFwHufdU5yX2v2oQ1CLSbAPe+6hzl3ldtwhoE2k2Ae1+75SjngwACugANdXQN5hFAAAEE2laAD+9tm7WcGAK+AB/cky8E7n3JLqxFoF0EuPcl5yT3vmQX1iLQLgLc+6pzkvtetQlrEGg3Ae591TnKva/ahDUItJsA9752y1HOBwEEdAEa6ugazCOAAAIItK0AH97bNms5MQR8AT64J18I3PuSXViLQLsIcO9LzknufckurEWgXQS491XnJPe9ahPWINBuAtz7qnOUe1+1CWsQaDcB7n3tlqOcDwII6AI01NE1mEcAAQQQaFsBPry3bdZyYgj4AnxwT74QuPclu7AWgXYR4N6XnJPc+5JdWItAuwhw76vOSe571SasQaDdBLj3Veco975qE9Yg0G4C3PvaLUc5HwQQ0AVoqKNrMI8AAggg0LYCpg/vVPbbNss5sTYVoCyny1i80nmRGgFXBSjL6XIGr3RepEbAVQHKsn3OYGVvRUoEXBegPNvnEFb2VqREwGUBU1mWmHl273LOERsCCGQVoKFOVkG2RwABBBAohYCpwk9lvxTZR5AIhAKU5ZDCagYvKyYSIeC8AGU5XRbhlc6L1Ai4KkBZts8ZrOytSImA6wKUZ/scwsreipQIuCxgKssSM8/uXc45YkMAgawCNNTJKsj2CCCAAAKlEDBV+KnslyL7CBKBUICyHFJYzeBlxUQiBJwXoCynyyK80nmRGgFXBSjL9jmDlb0VKRFwXYDybJ9DWNlbkRIBlwVMZVli5tm9yzlHbAggkFWAhjpZBdkeAQQQQKAUAqYKP5X9UmQfQSIQClCWQwqrGbysmEiEgPMClOV0WYRXOi9SI+CqAGXZPmewsrciJQKuC1Ce7XMIK3srUiLgsoCpLEvMPLt3OeeIDQEEsgrQUCerINsjgAACCJRCwFThp7JfiuwjSARCAcpySGE1g5cVE4kQcF6Aspwui/BK50VqBFwVoCzb5wxW9lakRMB1AcqzfQ5hZW9FSgRcFjCVZYmZZ/cu5xyxIYBAVgEa6mQVZHsEEEAAgVIImCr8VPZLkX0EiUAoQFkOKaxm8LJiIhECzgtQltNlEV7pvEiNgKsClGX7nMHK3oqUCLguQHm2zyGs7K1IiYDLAqayLDHz7N7lnCM2BBDIKkBDnayCbI8AAgggUAoBU4Wfyn4pso8gEQgFKMshhdUMXlZMJELAeQHKcroswiudF6kRcFWAsmyfM1jZW5ESAdcFKM/2OYSVvRUpEXBZwFSWJWae3bucc8SGAAJZBWiok1WQ7RFAAAEESiFgqvBT2S9F9hEkAqEAZTmksJrBy4qJRAg4L0BZTpdFeKXzIjUCrgpQlu1zBit7K1Ii4LoA5dk+h7CytyIlAi4LmMqyxMyze5dzjtgQQCCrAA11sgqyPQIIIIBAKQRMFX4q+6XIPoJEIBSgLIcUVjN4WTGRCAHnBSjL6bIIr3RepEbAVQHKsn3OYGVvRUoEXBegPNvnEFb2VqREwGUBU1mWmHl273LOERsCCGQVoKFOVkG2RwABBBAohYCpwk9lvxTZR5AIhAKU5ZDCagYvKyYSIeC8AGU5XRbhlc6L1Ai4KkBZts8ZrOytSImA6wKUZ/scwsreipQIuCxgKssSM8/uXc45YkMAgawCNNTJKsj2CCCAAAKlEDBV+KnslyL7CBKBUICyHFJYzeBlxUQiBJwXoCynyyK80nmRGgFXBSjL9jmDlb0VKRFwXYDybJ9DWNlbkRIBlwVMZVli5tm9yzlHbAggkFWAhjpZBdkeAQQQQKAUAqYKP5X9UmQfQSIQClCWQwqrGbysmEiEgPMClOV0WYRXOi9SI+CqAGXZPmewsrciJQKuC1Ce7XMIK3srUiLgsoCpLEvMPLt3OeeIDQEEsgrQUCerINsjgAACCJRCwFThp7JfiuwjSARCAcpySGE1g5cVE4kQcF6Aspwui/BK50VqBFwVoCzb5wxW9lakRMB1AcqzfQ5hZW9FSgRcFjCVZYmZZ/cu5xyxIYBAVgEa6mQVZHsEEEAAgVIImCr8VPZLkX0EiUAoQFkOKaxm8LJiIhECzgtQltNlEV7pvEiNgKsClGX7nMHK3oqUCLguQHm2zyGs7K1IiYDLAqayLDHz7N7lnCM2BBDIKkBDnayCbI8AAgggUAoBU4Wfyn4pso8gEQgFKMshhdUMXlZMJELAeQHKcroswiudF6kRcFWAsmyfM1jZW5ESAdcFKM/2OYSVvRUpEXBZwFSWJWae3bucc8SGAAJZBWiok1WQ7RFAAAEESiFgqvBT2S9F9hEkAqEAZTmksJrBy4qJRAg4L0BZTpdFeKXzIjUCrgpQlu1zBit7K1Ii4LoA5dk+h7CytyIlAi4LmMqyxMyze5dzjtgQQCCrAA11sgqyPQIIIIBAKQRMFX4q+6XIPoJEIBSgLIcUVjN4WTGRCAHnBSjL6bIIr3RepEbAVQHKsn3OYGVvRUoEXBegPNvnEFb2VqREwGUBU1mWmHl273LOERsCCGQVoKFOVkG2RwABBBAohYCpwk9lvxTZR5AIhAKU5ZDCagYvKyYSIeC8AGU5XRbhlc6L1Ai4KkBZts8ZrOytSImA6wKUZ/scwsreipQIuCxgKssSM8/uXc45YkMAgawCNNTJKsj2CCCAAAKlEDBV+KnslyL7CBKBUICyHFJYzeBlxUQiBJwXoCynyyK80nmRGgFXBSjL9jmDlb0VKRFwXYDybJ9DWNlbkRIBlwVMZVli5tm9yzlHbAggkFWAhjpZBdkeAQQQQKAUAqYKP5X9UmQfQSIQClCWQwqrGbysmEiEgPMClOV0WYRXOi9SI+CqAGXZPmewsrciJQKuC1Ce7XMIK3srUiLgsoCpLEvMPLt3OeeIDQEEsgrQUCerINsjgAACCJRCwFThp7JfiuwjSARCAcpySGE1g5cVE4kQcF6Aspwui/BK50VqBFwVoCzb5wxW9lakRMB1AcqzfQ5hZW9FSgRcFjCVZYmZZ/cu5xyxIYBAVgEa6mQVZHsEEEAAgVIImCr8VPZLkX0EiUAoQFkOKaxm8LJiIhECzgtQltNlEV7pvEiNgKsClGX7nMHK3oqUCLguQHm2zyGs7K1IiYDLAqayLDHz7N7lnCM2BBDIKkBDnayCbI8AAgggUAoBU4Wfyn4pso8gEQgFKMshhdUMXlZMJELAeQHKcroswiudF6kRcFWAsmyfM1jZW5ESAdcFKM/2OYSVvRUpEXBZwFSWJWae3bucc8SGAAJZBWiok1WQ7RFAAAEESiFgqvBT2S9F9hEkAqEAZTmksJrBy4qJRAg4L0BZTpdFeKXzIjUCrgpQlu1zBit7K1Ii4LoA5dk+h7CytyIlAi4LmMqyxMyze5dzjtgQQCCrAA11sgqyPQIIIIBAKQRMFX4q+6XIPoJEIBSgLIcUVjN4WTGRCAHnBSjL6bIIr3RepEbAVQHKsn3OYGVvRUoEXBegPNvnEFb2VqREwGUBU1mWmHl273LOERsCCGQVoKFOVkG2RwABBBAohYCpwk9lvxTZR5AIhAKU5ZDCagYvKyYSIeC8AGU5XRbhlc6L1Ai4KkBZts8ZrOytSImA6wKUZ/scwsreipQIuCxgKssSM8/uXc45YkMAgawCNNTJKsj2CCCAAAKlEDBV+KnslyL7CBKBUICyHFJYzeBlxUQiBJwXoCynyyK80nmRGgFXBSjL9jmDlb0VKRFwXYDybJ9DWNlbkRIBlwVMZVli5tm9yzlHbAggkFWAhjpZBdkeAQQQQKAUAqYKP5X9UmQfQSIQClCWQwqrGbysmEiEgPMClOV0WYRXOi9SI+CqAGXZPmewsrciJQKuC1Ce7XMIK3srUiLgsoCpLEvMPLt3OeeIDQEEsgrQUCerINsjgAACCJRCwFThp7JfiuwjSARCAcpySGE1g5cVE4kQcF6Aspwui/BK50VqBFwVoCzb5wxW9lakRMB1AcqzfQ5hZW9FSgRcFjCVZYmZZ/cu5xyxIYBAVgEa6mQVZHsEEEAAgVIImCr8VPZLkX0EiUAoQFkOKaxm8LJiIhECzgtQltNlEV7pvEiNgKsClGX7nMHK3oqUCLguQHm2zyGs7K1IiYDLAqayLDHz7N7lnCM2BBDIKkBDnayCbI8AAgggUAoBU4Wfyn4pso8gEQgFKMshhdUMXlZMJELAeQHKcroswiudF6kRcFWAsmyfM1jZW5ESAdcFKM/2OYSVvRUpEXBZwFSWJWae3bucc8SGAAJZBWiok1WQ7RFAAAEESiFgqvBT2S9F9hEkAqEAZTmksJrBy4qJRAg4L0BZTpdFeKXzIjUCrgpQlu1zBit7K1Ii4LoA5dk+h7CytyIlAi4LmMqyxMyze5dzjtgQQCCrAA11sgqyPQIIIIBAKQRMFX4q+6XIPoJEIBSgLIcUVjN4WTGRCAHnBSjL6bIIr3RepEbAVQHKsn3OYGVvRUoEXBegPNvnEFb2VqREwGUBU1mWmHl273LOERsCCGQVoKFOVkG2RwABBBAohYCpwk9lvxTZR5AIhAKU5ZDCagYvKyYSIeC8AGU5XRbhlc6L1Ai4KkBZts8ZrOytSImA6wKUZ/scwsreipQIuCxgKssSM8/uXc45YkMAgawCNNTJKsj2CCCAAAKlEDBV+KnslyL7CBKBUICyHFJYzeBlxUQiBJwXoCynyyK80nmRGgFXBSjL9jmDlb0VKRFwXYDybJ9DWNlbkRIBlwVMZVli5tm9yzlHbAggkFWAhjpZBdkeAQQQQKAUAqYKP5X9UmQfQSIQClCWQwqrGbysmEiEgPMClOV0WYRXOi9SI+CqAGXZPmewsrciJQKuC1Ce7XMIK3srUiLgsoCpLEvMPLt3OeeIDQEEsgrQUCerINsjgAACCJRCwFThp7JfiuwjSARCAcpySGE1g5cVE4kQcF6Aspwui/BK50VqBFwVoCzb5wxW9lakRMB1AcqzfQ5hZW9FSgRcFjCVZYmZZ/cu5xyxIYBAVgEa6mQVZHsEEEAAgVIImCr8VPZLkX0EiUAoQFkOKaxm8LJiIhECzgtQltNlEV7pvEiNgKsClGX7nMHK3oqUCLguQHm2zyGs7K1IiYDLAqayLDHz7N7lnCM2BBDIKkBDnayCbI8AAgggUAoBU4Wfyn4pso8gEQgFKMshhdUMXlZMJELAeQHKcroswiudF6kRcFWAsmyfM1jZW5ESAdcFKM/2OYSVvRUpEXBZwFSWJWae3bucc8SGAAJZBWiok1WQ7RFAAAEESiFgqvBT2S9F9hEkAqEAZTmksJrBy4qJRAg4L0BZTpdFeKXzIjUCrgpQlu1zBit7K1Ii4LoA5dk+h7CytyIlAi4LmMqyxMyze5dzjtgQQCCrAA11sgqyPQIIIIBAKQRMFX4q+6XIPoJEIBSgLIcUVjN4WTGRCAHnBSjL6bIIr3RepEbAVQHKsn3OYGVvRUoEXBegPNvnEFb2VqREwGUBU1mWmHl273LOERsCCGQVoKFOVkG2RwABBBAohYCpwk9lvxTZR5AIhAKU5ZDCagYvKyYSIeC8AGU5XRbhlc6L1Ai4KkBZts8ZrOytSImA6wKUZ/scwsreipQIuCxgKssSM8/uXc45YkMAgawCNNTJKsj2CCCAAAKlEDBV+KnslyL7CBKBUICyHFJYzeBlxUQiBJwXoCynyyK80nmRGgFXBSjL9jmDlb0VKRFwXYDybJ9DWNlbkRIBlwVMZVli5tm9yzlHbAggkFWAhjpZBdkeAQQQQKAUAqYKP5X9UmQfQSIQClCWQwqrGbysmEiEgPMClOV0WYRXOi9SI+CqAGXZPmewsrciJQKuC1Ce7XMIK3srUiLgsoCpLEvMPLt3OeeIDQEEsgrQUCerINsjgAACCJRCwFThp7JfiuwjSARCAcpySGE1g5cVE4kQcF6Aspwui/BK50VqBFwVoCzb5wxW9lakRMB1AcqzfQ5hZW9FSgRcFjCVZYmZZ/cu5xyxIYBAVgEa6mQVZHsEEEAAgVIImCr8VPZLkX0EiUAoQFkOKaxm8LJiIhECzgtQltNlEV7pvEiNgKsClGX7nMHK3oqUCLguQHm2zyGs7K1IiYDLAqayLDHz7N7lnCM2BBDIKkBDnayCbI8AAgggUAoBU4Wfyn4pso8gEQgFKMshhdUMXlZMJELAeQHKcroswiudF6kRcFWAsmyfM1jZW5ESAdcFKM/2OYSVvRUpEXBZwFSWJWae3bucc8SGAAJZBWiok1WQ7RFAAAEESiFgqvBT2S9F9hEkAqEAZTmksJrBy4qJRAg4L0BZTpdFeKXzIjUCrgpQlu1zBit7K1Ii4LoA5dk+h7CytyIlAi4LmMqyxMyze5dzjtgQQCCrAA11sgqyPQIIIIBAKQRMFX4q+6XIPoJEIBSgLIcUVjN4WTGRCAHnBSjL6bIIr3RepEbAVQHKsn3OYPW11fz589VHH32kxKNLly5qkUUWUV27dvX/2Wvapfziiy/UZ5995v+TeXm2sOyyy6qFFlrIbgcWqWbNmqW++uor9c1vflMtuuii/vlYbFY3yeeff67mzZunxGvxxRdX3bp1q7sNCfIToDzbW2Nlb0VKBFwWMJVliZln9y7nHLEhgEBWARrqZBVkewQQQACBUgiYKvxU9kuRfQSJQChAWQ4prGbwsmIiEQLOC1CW02URXum8SI2AqwKUZfucwUqp2267TR1wwAFq7ty5VXDiIw1dgn9Bw5dgOWgEI41s5BmBNGSRRjjSkCX4FzRsCZa//PLLquN0795djR07VvXr16/qvTQr5syZowYOHKgmTZoU2UziC2LWz0Gfl3OVGPV4ZV5flsY/wSQNms455xx19NFHB6t4LViA8myfAVjZW5ESAZcFTGVZYubZvcs5R2wIIJBVgIY6WQXZHgEEEECgFAKmCj+V/VJkH0EiEApQlkMKqxm8rJhIhIDzApTldFmEVzovUiPgqgBl2T5nsFJqwIABauLEifZoLUo5ZswYNWrUqEx7v/vuu9Wuu+6aaR9pNt52223VuHHj0mxC2hYKUJ7tcbGytyIlAi4LmMqyxMyze5dzjtgQQCCrAA11sgqyPQIIIIBAKQRMFX4q+6XIPoJEIBSgLIcUVjN4WTGRCAHnBSjL6bIIr3RepEbAVQHKsn3OYKXUGmusod544w17tBalvOaaa9T++++fae+XXnqpGj58eKZ9pNl4v/32U9dee22aTUjbQgHKsz0uVvZWpETAZQFTWZaYeXbvcs4RGwIIZBWgoU5WQbbvOAHp/lZ+ofPKK6+o6dOnR/7NmDHD7xpXxqSWf8stt5z/b+2111ZbbbWV2mKLLRj3ueOuGE7YFQFThZ/Kvis5RBwI2AlQlu2cglR4BRK8IlBuAcpyuvzDK50XqRFwVYCybJ8zWCk1cuRIdcEFFyh9WCd7weak7NOnj3rggQfU8ssvn2mHTz/9tNp6663VJ598kmk/NhsvueSSfsz9+/e3SU6aHAQoz/bIWNlbkRIBlwVMZVli5tm9yzlHbAggkFWAhjpZBdm+IwQ+/vhjdf/996s///nP6t5771UffvhhQ+e9yCKLqE033VRJl7Iybvaaa67Z0H7YCIEyCEglulYlO+9zMMVCZT/vnOB4CGQToCyn88MrnRepEXBVgLKcLmfwSudFagRcFaAs2+cMVl9bffrpp2rOnDlq3rx5Sn5oJ8/zZs6cqWbNmuX/4O6ZZ55RDz30kProo4/scb2UPXr0ULvssovq27evWmmlldQKK6ygFltsMSXP+YJ/3bt3V9LopVmTxP/uu+/6sX/wwQfq9ddfV9KA56677lLTpk1LfZh11llHbb755mqzzTZTK6+8sn8Och49e/ZU3/zmN1Pvjw1aJ0B5trfFyt6KlAi4LGAqyxIzz+5dzjliQwCBrAI01MkqyPZtLfDggw+qCy+8UI0fP17Nnz+/qecqlQ9psPPzn//cH3daPtgzIdAOAk8++aT6xS9+oSZPnuz3JHXdddepVVZZpfBTM1X4qewXnjUEgEAqAcpyKi5jg0nufekcSY1A0QLc+9LlAF7pvEiNgKsClGX7nMHK3koa6my//fbWG+y7777qqquuUl27drXeppUJpcega71hqkaMGOE3Sqp1LGk8dOihh6qDDjpI9erVq1ZS3nNIgPJsnxlY2VuREgGXBUxlWWLm+ZXLOUdsCCCQVYCGOlkF2b4tBZ599ll17LHHqrFjxxrPb+GFF1a9e/f2h7OSX9Mss8wyaumll/YrDvJLnffff9//98ILL6gnnnhCzZ0717gv2X7MmDFqn332MX6hZtyYNxBwSEB+8bXWWmupqVOnhlENGTJE3XrrreFyUTOmCj+V/aJyhOMi0JgAZTmdG17pvEiNgKsClOV0OYNXOi9SI+CqAGXZPmewsrf6xz/+4fcsY7OF9D7z6KOPqkUXXdQmea5pbrzxRjV06FDjMQcOHKiuueYateqqqxrT8IabApRn+3zByt6KlAi4LGAqyxIzz+5dzjliQwCBrAI01MkqyPZtJSCNC04++WQlH3aTKgDSMGfPPfdU3/ve9/zubqWbW5tJGi/Ig4CJEyf6vfOMGzcuccxs2e+ll16qNtlkE5vdkgYB5wSkF6odd9wxEtfGG2+spHvpoidThT+prBcdK8dHAAGzAGXZbJP0Dl5JKqxDoHwClOV0eYZXOi9SI+CqAGXZPmewsrf6zW9+o4YNG2a1we23364GDx5slbaIRNIYZ8KECVWH3mijjfwfDdo+t6zaASsKFaA82/NjZW9FSgRcFjCVZYmZZ/cu5xyxIYBAVgEa6mQVZPu2EZAGMiNHjqwa4qpLly7+0FRHHHGEGjBgQFPO97XXXlPnn3++kiGB4j3tLLTQQurII49U55xzjpJjMyFQJoGDDz5Y/e53v4uEPGjQIHXnnXdG1hWxYKrwU9kvIjc4JgKNC1CW09nhlc6L1Ai4KkBZTpczeKXzIjUCrgpQlu1zBit7K/kB3m233VZ3AxmiXnrLXnLJJeumLSqBPMc877zzIodfaqml1KRJk9Qaa6wRWc9CeQQoz/Z5hZW9FSkRcFnAVJYlZp7du5xzxIYAAlkFaKiTVZDtSy/wxRdfqOHDh6srrrgici6LL764Ovzww/1/q6yySuS9Zi3IB/7LLrvM70Xnvffei+x21113Vbfccovq1q1bZD0LCLgqID1H9ejRQ82cOTMS4g033OAP6xZZWcCCqcJPZb+AzOCQCGQQoCynw8MrnRepEXBVgLKcLmfwSudFagRcFaAs2+cMVvZW3/nOd9SMGTPqbiC91YwfP75uuiITSK/go0ePjoTgyjOYSFAspBKgPNtzYWVvRUoEXBYwlWWJmWf3LuccsSGAQFYBGupkFWT7UgvMmjVL7bHHHurhhx+OnMdOO+3kN9zJaxxnieOAAw5Qd999dySOfv36qXvuuUctt9xykfUsIOCiwNixY9UOO+wQCe2b3/ymeuedd5z4BZqpwk9lP5JlLCDgvABlOV0W4ZXOi9QIuCpAWU6XM3il8yI1Aq4KUJbtcwYrO6uXX35ZrbvuulaJzzjjDHXSSSdZpS0qUbx3IOn9R57ByLMYpvIKUJ7t8w4reytSIuCygKksS8w8u3c554gNAQSyCtBQJ6sg25dW4KWXXlI/+tGP1JQpU8JzkA+y0rPOfvvtF67Lc+aiiy5Sxx57rPrss8/Cw6611lrqgQceUKuvvnq4jhkEXBQ45JBD1FVXXRUJTXqGuuuuuyLrilowVfip7BeVIxwXgcYEKMvp3PBK50VqBFwVoCynyxm80nmRGgFXBSjL9jmDlZ3V5Zdfrg477DCrxI8++qjacsstrdIWlUh+YPjWW2+Fh993333VddddFy4zU04ByrN9vmFlb0VKBFwWMJVliZln9y7nHLEhgEBWARrqZBVk+1IKTJ8+XW222WZKXoNJhuyRHm369u0brCrk9amnnlJDhgyJNCBaYYUV1L333lt4bIWAcNBSCMiwV9J9tAznpk833nij2nvvvfVVhc2bKvxU9gvLEg6MQEMClOV0bHhFvebPn68++ugjJS5dunRRiyyyiOratav/L5oy+5IMryqNr+WfzMvfm2WXXVYttNBC2Xf+3z1Ir4xfffWV/6vpRRdd1D+fZuxc/q7PmzdPiZcMB8tQrM1QzbYPynI6P7zSeZEaAVcFKMv2OYOVndXgwYPVHXfcUTex1H1mz57dkjpi3YNbJnjzzTerftR33333qZ133tlyDyRzVYDybJ8zWNlbkRIBlwVMZVli5tm9yzlHbAggkFWAhjpZBdm+dALypcOAAQPU3//+90js22+/vd9zTTO/PIkcIMXCyJEj1XnnnRfZQrqvffbZZ9Vqq60WWc8CAi4IPPTQQ0rKkD5JD1XvvvuuWmKJJfTVhc2bKvxU9gvLEg6MQEMClOV0bHgt8Lrtttv8oUbnzp27YOV/58RJGroE/+RvWDAfvEqjHqknyt8NacgiDXCkIUvwL2jYEix/+eWXVcfp3r27kqEiZXjTLNOcOXPUwIED1aRJkyK7kfiCePVz0OflXCVGPV6Z15el8U8wSYOmc845Rx199NHBKl4LEKAsp0PHK50XqRFwVYCybJ8zWNW3kjrc8ssvr2bOnFk38bbbbqvGjRtXN12RCX7/+9+rAw88MAxB6oDSuEjqfUzlFqA82+cfVvZWpETAZQFTWZaYeXbvcs4RGwIIZBWgoU5WQbYvncDQoUOV9PKRNEkXsddcc01Tf+mcdJxa62QM7FNOOSUxiXS5+8gjjxQaX2JgrOx4gUMPPVT99re/jTi4NOyVBGaq8FPZj2QbCwg4L0BZTpdFeC3wkobaEydOXLCioLkxY8aoUaNGZTq69AIpf2fzmsrwZVVeFkUdh7KcTh6vdF6kRsBVAcqyfc5gVd9q8uTJqnfv3vUTeil++ctfqpNPPtkqbVGJ5BnmDTfcEB5+66239p8ZhiuYKa0A5dk+67CytyIlAi4LmMqyxMyze5dzjtgQQCCrAA11sgqyfakE5NfAxx13XCRm+ZWw/ovnIhvrnHnmmeqkk06qGd9ZZ52ljj/++EgaFhAoUkCG85Bhr957771IGDfddJP66U9/GllX5IKpwk9lv8hc4dgIpBegLKczw2uB1xprrKHeeOONBSsKmpNG4fvvv3+mo1966aVq+PDhmfaRZuP99ttPXXvttWk2IW2TBSjL6UDxSudFagRcFaAs2+cMVvWtLr74YjVixIj6Cb0U0rh7q622skpbVKKePXuqt99+Ozy8/Ojv9NNPD5eZKa8A5dk+77CytyIlAi4LmMqyxMyze5dzjtgQQCCrAA11sgqyfWkEHnvsMX/Iq6Arf+kS9vHHH1dvvfWWGjJkiD+EQXAyRTTWkQY4J554YhCC/yrDX0lsm2yySdgIQoZd+Nvf/qb69OkTSZt14aOPPvJ7HGn2MEUyNMQHH3yglltuOXoCyppJjm4v3UFvt912keikq2WXhr2S4EwVfir7kaxjAQHnBSjL6bIIrwVeMrToBRdcoIK64IJ38puT+tsDDzzgD7uQ5ahPP/20kl9Nf/LJJ1l2Y7WtDL8qMffv398qPYlaI0BZTueKVzovUiPgqgBl2T5nsKpvNWjQIPWnP/2pbsJu3br5Q0h17dq1btqiEkyZMkWtueaakcOPHz/eHxo1spKFUgpQnu2zDSt7K1Ii4LKAqSxLzDy7dznniA0BBLIK0FAnqyDbl0agX79+6sknnwzjveKKK5QM1yOTfFAvsrGODIFwwgknhLHJjDTSOfroo/11Dz30kNpxxx3DL5bWXXdd9dRTTyl5eJBleu655/zufJ944gk1Y8YMf1ff/e531UYbbeQ3BDr44IP9nlJsj/Hpp5+q22+/XT3//PPqlVdeUa+++qp68803lfS4Ig035CFCr1691DrrrKMkP37wgx8YG0/YHpN0xQvstttu6q677ooE8uMf/9jqAVhkoxYvmCr8VPZbDM/uEWiyAGU5HSheUS+pq8yZM0fNmzfPb6T98ccfq5kzZ6pZs2b5dZdnnnlGSb1LGjCnmXr06KF22WUX1bdvX7XSSiupFVZYQS222GJKGlgH/7p3766k0UuzJmkMLY1iJXZpFP36668racAjf5OnTZuW+jBSP9t8883VZpttplZeeWX/HOQ85NfaUo9jKlaAspzOH690XqRGwFUByrJ9zmBV20o+98sPyKTeVG8qw5Cfv/vd75Q8swsmqatJfZA6WyBS7lfKs33+YWVvRUoEXBYwlWWJmWf3LuccsSGAQFYBGupkFWT7Ugjceeedao899ghj3WeffSLjOMsbRTXW+dWvflU1lJXeSCcI+owzzlDSjW0wDRs2TF1yySXBYurX0047Tck+a/2qXL5gOvbYY/3j1qosyRdcMgSDxCPzttPGG2/sx/DDH/7QdhPSOSYwd+5cJV88xq+jm2++We21115ORWu6hqnsO5VNBINAXQHKcl2iSAK8IhxWC9JQZ/vtt7dKK4mkJ8arrrpKufKra/mbLMNUydAO0iip1iR/w6Xh+kEHHeQ3pq6VlveKFaAsp/PHK50XqRFwVYCybJ8zWNW2mjx5surdu3ftRP99V4aP0p+/WW2UcyJ5rinDjQfTgAED1IQJE4JFXksuQHm2z0Cs7K1IiYDLAqayLDHz7N7lnCM2BBDIKkBDnayCbO+8gPTmsv766/u9u0iwq666qnrxxRf9XznHg8+7sc7ZZ5+tRo0aFQkjqZGOJJAKyZZbbqn++te/+ukXWmgh9dJLL6m11147sr3NgjTSSTNu9X777aeuvvpq1aVLl8juv/zyS38/559/vnHohaCSVatCJQ7SIIipfALnnHOOOu644yKBS55LTwTy5Z9LU3AtxmOqdW3G07KMAALFC1CW0+UBXum8JPU//vEPv2cZmy2l95lHH31UyZCqrk033nijGjp0qDGsgQMHqmuuucavGxsT8YYzApTldFmBVzovUiPgqgBl2T5nsKptdfHFF/uNmGun+vrdRx55xB9i1CZtUWmkB8fp06eHhz/11FOVPOtjag8ByrN9PmJlb0VKBFwWMJVliZln9y7nHLEhgEBWARrqZBVke+cFrrzySvXzn/88jPPyyy+PLIdv/Hcmr8Y6SQ0cTI10ghjHjh2rdthhh2BRHXLIIUrOL830+OOPq6222iqs4MhQV5dddpn/y/EXXnjBH7bhrbfeqtrl6NGj1Yknnhiul55zpMcUiUmfpCvhAw88UElvOeutt54/zJW8L/uWBh3yK/Wk6YILLlBHHnlk0lusc1hAhmF7+eWXIxF+5zvfaWjIjchOWrBgqvBT2W8BNrtEoIUClOV0uHil85LUv/nNb5T0XGgzyZCfgwcPtklaSBppjJP062oZ5lSGPpXeE5nKIUBZTpdPeKXzIjUCrgpQlu1zBqvaVoMGDbIanluGjpo9e7aTjbCDM3zttdeqfrT38MMPq2222SZIwmvJBSjP9hmIlb0VKRFwWcBUliVmnt27nHPEhgACWQU6oqHO9ddf7zdmkLF6ZZxh6f3Dla7ps2ZgnttLDxnyC5RbbrlFrbnmmuqoo45y/kOg9PjSs2dPNWPGDJ9KGhC88cYbdT9wt7qxzq9//Wv1v//7v5Hsq9dIJ0jcr18/9eSTT/qL8uvtqVOnqhVXXDF4u+arVGo23HBDv9GMJJQeT2Rf0qAmmB544AG18847B4vhq3yRIw0yxPP555/3G/T861//Ct//1re+pY455hi/sc0SSywRrtdn5Pj777+/kjIZn7p166ZkfyussEL8LZYdFZg3b57/BV+8snzYYYf5X3K6Frapwh+P37W4iQcBBKIClOWoR70lvOoJVb+/5557qttuu636jdiaRRZZRL3//vtqySWXjL3jzuLIkSOV1DH1aamlllKTJk1Sa6yxhr6aeccFKMvpMgivdF6kRsBVAcqyfc5gZbaSz/zyo7JZs2aZE/33HWnkPH78+Lrpikzw29/+1h+6NIhBGhfJM295ZWoPAcqzfT5iZW9FSgRcFjCVZYmZZ/cu5xyxIYBAVoG2b6gzZcoU1atXLyXDHwXTmDFjqoYbCt7j1SwQHy5JPgD+85//dPohv/yCWD5kB1OaXlta1VhHviyRL030ybaRjmxz7733qh/+8Ifh5meeeaY64YQTwuVaM/fcc4/fwCZIc+utt6ohQ4YEi/6rlBX5wmnu3LmR9bLwy1/+Uu29996qf//+6t133w3f33XXXf2hE5ZeeulwnWlm2rRpfkMvaeQRn44//nh11llnxVez7KhAUoMzCVXyWBrFuTaZKvxU9l3LKeJBoLYAZbm2T/xdvOIi9Zflb1jQyLtW6jJ8kXPyyScr6RVRn2644Qa1zz776KuYL4EAZTldJuGVzovUCLgqQFm2zxmszFaTJ09WvXv3NifQ3pFh4k855RRtjXuzP/3pT/0fUQaRDRgwILEHxeB9XssnQHm2zzOs7K1IiYDLAqayLDHz7N7lnCM2BBDIKtD2DXVuvPFGNXTo0IjT97//fb+xQ2QlC3UF1lprLfX6669H0smwAJdccklknUsL0uvPhRde6IckPbW8+eabqbr4b3ZjHenNSXqd0ac0jXSC7fr06aOeeeYZf1Hmn3rqqeCtmq/So5R0hyuTNLb561//mpj+29/+tnrnnXeq3lt//fXVZ599pqSb3WCSYcUuvfRS1aVLl2BV3VfpsUd67olPrg6ZFI+T5a8FpCeml156KcLRo0ePyDjpkTcLXjBV+KnsF5wxjh7+888/VxMnTlSvvPKKf01Pnz49fJUv8OVeuOyyy/r/5NeZ8m/ttdf2hxbcYostlPQSxtQaAcpyOle80nlJ74EyrKPNdMYZZ6iTTjrJJmlhaeK9A0ljbKnj8YvrwrKk4QNTltPR4ZXOq5NTU+dzO/cpy/b5g5XZSnoHHzFihDmB9o784E8avrg8xRuVn3rqqUp+XMnUPgKUZ/u8xMreipRKUe9z9yowlWWJmGf37uYbkSGAQHaBtm+oc9FFF/lD8ehU8gXa3/72N30V8xYCMmSS9KCjT9J1vnxh6erD/tVXX91vnCMxDx8+3B+6S4/fZr5ZjXWkN5+jjz46cshGGunIDuLXtQwZteqqq0b2HV944YUX1AYbbBCuNv2a+quvvvLzUyqu9SbpYUd+qZ12+sUvfqGuuOKKxM0+/fRTvuBOlHFrpWnYq8MPP9xvuOVWtF9HY6rwU9l3MbeKienjjz9W999/v/rzn//sN+j98MMPGwpEhsPZdNNN/eE2DzjgAL8XsYZ2xEaJApTlRBbjSryMNIlvXH755UqGcLSZHn30UbXlllvaJC0sjdQP33rrrfD4++67r7ruuuvCZWbKI0BZTpdXeKXz6rTU1PnKk+OUZfu8wspstfvuu6s//vGP5gT/fUeebc6ePVvJMPOuTvJDEuk5Xp/kB3nbbLONvor5kgtQnu0zECt7q05NSb2vHDlvKssSPc/uy5GHRIkAAo0JtH1DnaRhhtL0QNIYa3tuJUNorofuAAA+zElEQVQsJf1q+Oabb1Z77bWXcyf9/PPPq4022iiMS4Z90oeMCt+wmMnaWEd69ZHeffSp0UY6sg/pxUR6Mwkm2X+9XwdJ3kkeyiS9QMjwREkPH95++23Vs2fPYNfG10MOOURdeeWVxvdrvSG/9pFGPkmTNCjSzy0pDeuKF0i6t0pU0uuI9Krj4mSq8FPZdzG38o3pwQcf9HtfGz9+vJo/f35TDy7XnfRmJr2PyTCB0oiHKZsAZTmdH17pvAYPHqzuuOOOuhtJr1nyRU7Xrl3rpi0qgfQkKY3W9em+++5T0rMhU/kEKMvp8gyvdF6dkpo6X/lymrJsn2dYma1WXHHFyPDtppTS2CXohdqUpuj18qM3+fFbMJWhcVEQK6/2ApRnrOwFSGkSoN5nknFzvem+J9Hy7N7NPCMqBBBojgANdZrj2BF7kYYd8qvcL7/8MnK+2223nRo7dmxknQsLo0ePDnt7kS9GZ82apbp3795waI021on3fiMBZGmkE5zAKqusov7973/7i0OGDFG33npr8FbiqwzJEgxZtf/++6trrrkmMZ00aNpll10S3wtWbrbZZkp+RZ7U0CdIU+tVehaSHoaSJqlEb7/99klvsc4hARkG7cUXX4xE5PKwVxKoqcJPZT+SjR218Oyzz6pjjz225t+whRdeWPXu3VtJb3wrrbSSWmaZZdTSSy/tf0iUvyvvv/++/08aGT7xxBNq7ty5RkPZfsyYMWqfffYxXo/GjXkjFKAshxRWM3hZMfmJ5O/B8ssvr2bOnFl3I2mAN27cuLrpikzw+9//Xh144IFhCFJvk8ZFrvaEGQbKTKIAZTmRxbgSLyNNR75Bna+82U5Zts87rJKt0gxrKsNHyQ/LXJ7iw5qWoXGRy56uxkZ5ts8ZrOytOiUl9b5y5rSpLMvZ8Oy+nHlK1AggYCng3eTaevr1r39d8Sgi/7weddr6nFt5ct4vcCOWYrvQQgtVpk6d2srDNrRvPdatt966oX3EN/K6yq14jX4iBt4QAhWv8VI8qb/sNdKJpBUvr5FOYtq0K70vXsJ9r7POOjU39xpUhGklhltuucWY/rjjjoukjZcfrzeezPn94x//2HiMxx57zBgbb7gh4A17VfEqz1V5OGzYMDcCNEQRv5aDZUNyVrexgDdcYGXo0KGJ17FcF17DnIrXoKbyyCOPVD755BNric8++6zy+OOP+9t6DQ79v4/Bdaa/fu9736s8/fTT1vslYVRAt9Tno6lYCgR0I30+eJ/XBQLPPfdc1d823Uyf93oGXLCho3Nyn9NjblZ92NHTbfuw9LzU59v+xBs8Qd1In29wd2xWUgHqfCXNOC1svfzq81oSZv8roPvo850O5PVAE6kP6Tbx+QkTJjjP5fUOFDkfr3GR8zETYHqB+LUZLKffU/tvEdjEX9v/zDnDuAD1vrhIuZbjZVhfLteZEC0CCCCQTkBaI7b1REOd5mbvH/7wh8gHwuAPpotfVnjDXoWxnnHGGU2DsG2sc/HFF4fHD5ya1UhHTua2224L9y+NpebMmWM8Rz0WSev1AGFM279//3C/Qdz66+23327c1vaN1VZbzXgM79dOtrshXUEC559/fmL+zZgxo6CI7A6rX8f6vN3WpGoXgUsuuaTi9SpRdQ136dKlMmjQoEozH86++uqrFW/Iq4o3RE7V8eRe7PUuVvniiy/ahTa389DLrz6fWwAlO5BupM+X7DRyCTepgbVups9PnDgxl5iyHGTllVeO3HtOOeWULLtj24IF9OtPny84LGcPrxvp884GTGBNF6DO13TSQnaol199vpBgHD+o7qPPOx52y8Pba6+9IvUh3Uaf93ocrMiPklye4j/Ck/ib+fnV5XPvtNj0a1Of7zQHm/PVffR5m21J0z4C1PvKn5d6+Y3Pl//sOAMEEEDALEBDHbMN7yQIzJ8/vyI9qsT/WK6++uqVr776KmGL4lZ5QxeEcUoDo2ZO9RrrSOUwbtTMRjpyLs8880zkGE899ZTxFAcPHhym9YatMqaTniPiPQbp57HbbrsZt7V9QxoJJfXGIsfxhphx/sGI7Xm2czpv2Kvwegquj+985zvOn3IQa/zV+cAJsCkCn3/+ud9oJp7/iy++eMUb/ipzT2G1gnzvvfcqp59+ekX/uxTEseuuu1Y+/fTTWpvzXkwgsIu/xpKx+F+BuFOwDFC1gNRzAp9ar9L4TurELk+vv/561bmMHz/e5ZCJrY6A6Zqss1nHvo1Xx2Z9hTpfe+U9Zdk+P7FKtpJnFSYbff2AAQOSd+DQ2t/85jeRcylD4yKH+EoVin5t6vOlOomcgtV99PmcDs9hChag3ldwBjTx8Hr5jc838TDsqoQC119/fUV6p1933XUrhx9+uPPP41wi/vDDDyvSicV6661X2WWXXSoPP/ywS+ERy38FaKjj8KUwe/bsyn/+85+KFCaXpiOOOCLywTD4w+lSIZfhR/TGIK341bOpsY7ee01g0+xGOnI9TJ8+PZIPY8eONV4m0ktEEMvo0aON6R588MEwXZA+eJXeJprR243eE1Cw7+B1ww03NMbGG24IyBeT0hNIkGfB6/Dhw90IsEYUQazx1xqb8FabCMycObMycODAqut2p512qkjXuHlNEodUiuPXYL9+/SrSmIfJTiDuFyzbbd15qQKf+GvnSdQ+Y2lwvswyy1SVz7ibLG+77ba1d+bAu1dddVXkXOSLnLlz5zoQGSE0KpB0Lco6pmQBvJJd2n0tdb72y2HKsn2eYlVtJT2cmlzi60899dTqHTi2Rv8RnsS/zTbbOBYh4TRLIH59BsvN2n877Sewib+20zlyLskC1PuSXcq6Nl6G9eWynhNxZxeQH6HJj/v162HMmDHZd9whe5D6rW4nzwbFlMktgbZ/sleGoa+effbZytlnn+3/0v/73/9+ZYMNNqgsscQSkQIkXxxsvfXWlV/84hcV+QXFc889V9iVFO/JJSjoQ4cOLSym+IGnTp0a8XvllVfiSZqynNRYJ/AIXlvRSEeClxbjemOkWr0GBcOvyDAr0gDMNI0aNSriFpyDvDbrS6kDDzzQeIyDDjrIFBrrHRG44IILEvNPGhW6PunXsz7vetzEl01AugdfY401ItetVEqvvfbabDvOsPWFF15Y6dq1aySmtdZaqzJlypQMe+2cTfXyq893jkC6M9WN9Pl0e2n/1FK31n1qzUsPWa5Pe++9d+R8yvArcddNi47PdE0WHZerx8fL1ZxpXVzU+VpnW+SeKcv2+lhVW8UbLpuMZL1LPz6sPpOK34t5vIfW0047LSkp69pAwHSttsGpNf0UsGo6aSl2SL2vFNmUKkhTWZb1TJ0rcOONN0aebcn1IN+hM9kJrLnmmlV+w4YNs9uYVLkJfEOO5F3cbTt5jSTUyJEjI+fXp08f5Q0TFFmX98K7776rvJ5X1C233KLeeOONhg7fq1cv5T2EV4cddpjyGvI0tI9GN9p0003V008/Hdl8scUWU96X9cprZBRZX8TC3/72N9W/f//w0B988IFaaqmlwuVmzvzpT39SQ4YMUV7DmardyvXnNY6pWt+sFSussILyemHwd+c9gFBeQ5dMu/Z6dVBPPvlk4j4uu+wy5TUUS3wvzcpVV11VvfXWW4mb3H777cr7hVDie6x0Q8Dr9Uj985//jATjdSWtpk2bFlnn4oLXsC0xrDb/M5h4zp2y0ut5THnD/Sl5DaYePXqou+++W/Xt2zdYVcir1EPkb4fXOCc8vtzT77333sJjCwNydIaynC5j8LLzknr5iBEjrBI/8sgjymtAb5W2qEQrrbRS5N7n/YpGeV/mFBUOx22CAGU5HSJe6bzKnpo6X9lz0Bw/ZdlsE38Hq7iIUvvss4+66aabqt+IrVl00UWV96M25f2gI/aOO4svvPCC8n7YGQlowoQJymuMHVnHQnsIUJ7t8xEre6t2SUm9r11yMnoeprIsqXh2H7XqpKWkZ3VbbLGFku9/meoLJH2XJ9+Tz5gxw+l6b/0za7MU0lCnnSfXetTxGuhUjjrqqIrXqKWqJZt3aTW0TnrfkZ5QvMYouWXlJZdckhir/FrFhemBBx6IxCfDGbRy+tGPfhQ5nuTlOuus08pD+vteffXVw+PKkFJZJhliTYa3Ml2HXoOyLLv3t5WejUz7l2PPmjUr8zHYQesEZEi5pGGvZDi8Mkyma68MsRNjegEZ4mXzzTevuudsv/32lS+//DL9DluwxTHHHFMV35JLLllpxv22BeE6s0vKcrqswMvOa7fddqsqj0l20iPXvHnz7HZaUKqkYR5c/5V4QVSlOmzS9SjrmJIF8Ep2ace11PnaMVcXnBNleYFFvTmsqoW8hstW9bsy9DwYfw7brVs35+uk1TnCGlsByrOtlP8D9MRybr8HUpZJgHpfmXIrXaym+56sZ+pcAde+3y9bTowePTrxb+TNN99ctlNp63jb/i7nUkG+5557Kt6v5RMLhvzBkQf/gwYNqkhjF69Xk8q///3vigyLJUManXnmmZWdd965ZkMK+QB6//3353LByhig3i9Oqs7F68Uml+PXO8ijjz4aie3999+vt0nD78tQZF6L38jxgoqFNMpq5bTsssuGx/V+JZTpUF4PE+G+gviD19VWWy3TvoONL7roIuMxvN58gmS8OirgtWBOzL8yDHslpMH1HH91lJuwMgp4v5405vm+++5beGOdX/7yl8b4ttxyy8Ljy8jf0s3jZThYbulBS7zzwCf+WuJTanro0qBbhpmNGyUtDxw4sOnHb/YOr7zyysi5yGcMeaDJVG6BpOtR1jElC+CV7NKOa6nztWOuLjgnyvICi3pzWEWFXnvttUh9yOQj60855ZToxg4u7b777pHzKUOd1EHG0oRkul5LcwI5BopVjtgOHIp6nwOZ0KIQTGVZ1jN1roBL3++XMRfefvvtxDYF2223XRlPp21jbvu7nAsF2RsSqeINGRT5QKX/4ZGH5yeeeGJFejSpN0nBOvLIIysLL7ywcX+HH3545Ysvvqi3q8zv/+QnP0mM4eWXX86876w7eP755yOxeV3EZt1l4va1GukEedyqxjrSu4neQGj8+PGJMdqulF5Rgpjjrz/72c9sd1Mz3VZbbWU8hjckQ81tebN4Aa+rvKr884a9Kj4wywji13WwbLk5yUokcPbZZ1ddq/Eew4psrJPUmj0e31lnnVUi8XxDDcpu/DXfKMpztLhTsFyeM2h9pM8991zVPSNwir+efvrprQ8o4xH22muvyPmU4VfiGU+5IzaPX4vBckecfAMnGfjEXxvYFZs4LECdz+HMaVJo8TIcLDdp9221m8Am/tpWJ5niZORHkHEL03LW52kpwmooqTQqX2655SLnU4Y6aUMny0a+gOlahadaAKtqk3ZdQ72vXXP26/MylWVZz9S5Ai58v192fekAJF6+ZNSMqVOnlv3U2ib+tr/LFV2QpTFFra70+/bt21CBkIYoG2+8cVUBCwqcHLPV3fLHh5cKjn3ccccVXkCkN6IgHnltxYfupEY6cr397ne/izSgkeO3orHOtGnTIueYtYHU+uuvH9mf7ifnlHWSeJOGTQqO8/e//z3rIdi+hQKmYa9GjBjRwqM2d9fBtRZ/be5Rkvcmfu+9957/T4Z4+/jjjyvz589PTpxxrTTU/OSTTyqzZ8+uSG9iMuSiNBhNO8nDQOk9TbaXV2lMKj0ytGIoQRmKSvYtxwhilnNoZJIe1fR7jfT+NmnSpMof//jHyiKLLBK5zxXRWEd6yItfg+edd15FGuIuv/zy4XsS61NPPdUIQc1txPijjz6qmaaRN+Uaf+edd3LpCSjuFyw3EncnbBP4xF874dxtz7FWj39xtwkTJtjutrB0PXr0CO8lEj+NoQvLiqYeOH4tBstNPUgb7Szwib+2+hSp89UWps6XX51PcoJ6X+3rsd3ejd/vguV2O0/b89l7770j9aHAI/4qnxdd73lw8uTJVefyyCOP2FKQroQC8es0WC7hqbQ85MAm/tryA3sHoN5XW5l6X371vnau80nZZupcgaK/328HeRmxJ/43Upalt38mNwS+IWF4mdK2k/fllxo5cmTk/Pr06aO8L78i61qx4H0Jq/bYYw/1l7/8JXH33//+99Xtt9+uFl988cT36630vmhTXoMc5TVCSUy67bbbqnvvvVd5PfYkvp91pfdlrVp11VWV9+ViZFfelwPKayijvN4BIuvzXPj0009V9+7d5a+4f9hbbrlF7bnnnk0L4bLLLlPDhg0L9y87Pvfcc8Nr7eqrr1YHH3xw5H2vsY46//zzmxbDM888o+RaDia5HpZYYolgMdWr14BArbjiipF49R28+uqraq211tJXpZ73hk1SXqOOxO28obXUG2+8kfgeK90Q8Bqm+dd8PBrvi3nlDekXX+3kstcDVWJcwX0i8c0mrBw7dqzyuqlWXuOcqr1JTF27dvXv094DQhX8k/u2zMt7XoMN/34qcXoNbvx/8vdF/nkNMv1Xfd77IFx1HNnXXXfdpXbaaaeq95JWSL56wy+p119/PeltP6YgxqSYJW6v5zd/W6/hkPIeXvj/9Dj1eTmv+CQ2xx57rPrVr34Vf6vmsjeMnvKGjwzTXHHFFerQQw/1l//0pz+pIUOG+IZBAq+xjrrmmmuU17gnWNWy1zFjxqgTTjghsn+ppxx99NH+uoceekjtuOOOSv6+yrTuuuv69ZVu3br5y43+5/UWorzKt3riiSfUjBkz/N1897vfVRtttJH/d0T+Xnm9Y1nvXv7GSv3FazSsXnnlFSV/I958800leS3XxZprrql69eql1llnHSX58YMf/ECZyp/1QbWEpn21uixrIZRqFq/62SX3aK8xX92Ecn17jSD9+3PdxAUlkDIp5U+fHn74YbXNNtvoq5gvoQBlOV2mFeFFnY86X3CVFlXnk+NT7wtyofNei7jvuazcs2fPqueVSfFuvfXWymv0kvSWM+viz9Pk8+EHH3zgdJ3UGbySBkJ5ts+4oqyo91HvC67Soup9nVLnE2ee9wVXW+e9Fvn9frtoy/cy8tzf+yF25JRWX311/7sf09/RSGIWWivg3eTaeiqyxd0BBxyQ2FLNy9GK90GwoR4O4pnlfdFZ8R68G48jvQW0cpIhu+R84v+8xkmtPKzVvr0bTRjXSSedZLWNTaKknnTOOeecqk1b3bPO9ddfH56f1yip6vhpVtx5553hvuJ5+e1vfzvNroxp/9//+3/GY4waNcq4HW+4IeB9oV+VfyuttJIbwVlGEb+2g2XLzRtOFh9LPjhu3q9eYxDrc7jyyiur8jvveOV4G2ywgXXMkvCOO+6IxC1jV8enonrW8T64R2KT85OedOKTtGbXrb1GofEkqZalJw29hyF938H8YostVjnttNPq9pYkvR1JumWXXTYSY7Af06v0AHjPPfekirtWYtNxam3Tye/hVT/3vQanVte01Lldny6//PLIuXiNi1rey6brJu0SH2U5XU4W4UWdr/q5gCkf4uup86lK1jqflBDqfenuE+2WOl6uguV2O0+b8/F+cBKpDwUWSa+nnHKKzS4LTRPvqX3gwIGFxsPBWy+QdK3KOqZqgaKsqPdR75OrkWd9rX/Wx72v+r7XSWuK/H6/nZyPOOKIxLqx98O+djrN0p5L29fwiirIN954Y+KFL39Yll566cpbb73VtItm+vTpkeEy4hXUSy65pGnHiu/otddeqxrmSY4/aNCgeNLclyWGwGKzzTZryvGTGunI+KimqZWNdeQL6OD8vF4LTCFYrR8+fHi4r2CfwetPfvITq33USiRDkXktM43HePbZZ2ttznsFC0hXrklf9B955JEFR5bu8ME1HX9Nt5f0qbfYYgvjtR+PpZXLSQ0KTWdz8sknOxHzdtttZwqxar0M77X22muHcXs9vvlDgFUl9Fbk3VjH6xUojCvI46RGOhKrDC32ve99L0wvZc/rISPpNOquky9rguPZvO63334VGTotPsk6uSa8HgCN+5N7fK37vBy/1t/L+DFrLZvOpdY2nfweXrVz/6WXXjJe13E7aajm+uT1GhY5nzI0LnLd1JX44tdjsOxKfK7FEfjEX1sZJ3W+xr+woc6n/M9bjdb55Lqm3tfK0l2Ofcfvd8FyOaJvbpTyLC44/3qv48aNa+7Bm7w3GTpmmWWWiZzP6aef3uSjtHZ3MvSyDAFe5CTDj5dpMl23ZTqHvGItyop6H/U+nvV9fQ20+lmflHGmzhUo6vv9dhP3RmeJ1CWDv51Dhw5tt1Mt5fm0/V2uiILsDQFRkR5Ogos9/ipjwjV7uu+++4zH84ZNqfz9739v9iHD/Q0YMKDq2N6wJxVvOKUwTREzeq8E8kWn9ASQZUpqpCMVsnpTKxrryBe53lBVofshhxxSL4ya7yf1lhJctxdddFHNbW3eTKq4Bvv3hmew2QVpChSQaz/IL/313XffLTCq9IfWY9fn0+8p3RZnnXVWxRsGKtFQj6OV81LO/vWvf1kHPmHChMq3vvWtQmOWRq1//vOfrWP2hriKxCu9StSa8mqsIx9Y43lraqQTxPvggw9GtmnkHv/YY49FGs54Q11VpK4gDZqkceQqq6wSOUYQ4+jRo4Mw/Ff527n99ttXpV1uueUqxx13XMUbWrLidbfr99jhDcVW8YYWrciXbcH+4q8XXHBBZP+NLMT3GSw3sq9O2Cbwib92wrnbnGP83hF30pfl3uj6pNcPJfYyNC5y3dSV+PRrUZ93JT7X4tCN9PlWxkmdr7EvbKjzLXBrpM4n1zT1vlaW7PLsW7/X6fPlOYPmRar/sE23iM97wzhXvGF9m3fgFuxJPrvF4/aG6mrBkZqzS/m8OX78eP+HHt5w2hVvmK4w/iWXXLLSt2/fiuTPGWec4X8ubc5RzXuReKRhkzyTkZ6DyzLF8zxYLkv8ecYZ2MRfWx0D9b4F9Ze4fa1l6n0L3Bqp93VinU+uJ6bOFSji+/121e7Tp09YJwvu09LLvjSoZipWoO3vckUU5G233bbqgg8u/E033bRlOV5rCKx+/frVHdKi0cCuvfbaxPO98MILG91lU7aTD4aBu7zeeuutDe83qZGOVMhtp2Y31pEvRfVzu/fee21DqUrnjU0Y+TJX36/MS2vLrNN6660XiVc/hnw4rzVJ71Qbbrih/0WxfAnMlL9A7969q/KvbMNeiZp+3enzeYjKw7933nmnMnXq1Ip0wy0P2+QeJUM1STep0nNV2uGE5ByWWmqpivSCIvcoGVpIGmW+8MILFWkwKg1zpk2bVvHGrm/oFKUnJWmkIT1ivfHGG/5+H330Ub/xzKWXXlo58MADK2uttZbRVTfW56Xx6I9//OOK9PAjjWUef/zxyj//+U+/1xg5jhxPrNJM0uNLjx49wli8cVethnppdWOdc889N4wpMKjXSCc4b/3XWfIA+T//+U/wVt1Xacy5/vrrh8eWxsNyXejT/fffH74fxCavUkEPev2bPHlyRRr46O9LAy5pCFurEi/Hl6E39e2CeXlQmzZ/9bhlPthX/DWejuWvBeJOwTI+XwvstddexmsqsJLXMgwh9eKLL1adSxkaF3Et2gno16M+b7d156XSjfT5VktQ51vw5QN1vuohTpOuvyx1Ptkf9b4k1c5cp9/r9PlO1Fh55ZWr6kS6STC/1VZbOc8jP3QI4pVX+Tzl4rMx+Xx4/vnnV6RnWz3eevPSA7o0oKn1+bLRTJJeyjbffPMwHvlR6aRJkxrdXa7bmdxyDaIkByvSinof9b7g+uNZX+ue9YkxU+cKFPH9frtqy8g7wT1Lf73qqqva9ZRLc15tf5fLuyDHfwWvX/Ayf9NNN7Xs4ijq2HPmzKksscQSVYVcvtwvcpJfTehffP/sZz9rKJykRjpnnnlm6n01s7GO/uWvfAGb5UP6XXfdVZV3wXUrfvLgL8skDQeC/cVfZZgUabhgmuS8pNeGYDv5Up0pXwFpANEOw16JWnAdxV/zFTUf7fnnnzfGGI9ZlqWXk6K7b5YyauqZJSlmeWCapmcfs1b0HRlPVT9eml5bWtVYJ6n+YfvBXc7uL3/5S+Sc0vzdufvuuyPbJjVUlb+R+q8bdT9piDNlypTKCiusENnPrrvuat1l+dtvv+03bND3G8wff/zx0QxMuRTsJ/6acjcdkzzuFCx3DECdE5WGfYFJrVfpQdL1Kd4DXhkaF7lu6lJ8puvTpRhdisVlL+p8jV8p1Pmq7aj3VZt06hqX73t55on8MMZkEV8vw/u6PslnMD1u+XGoS5M8M5Qf8mTtkVeGWR4xYoT/w52s5yc/ODrhhBP8H6HodtKjTyt7nM8at769Hrc+r6dh/msB3Uefd8WHel/jOUG9L2rXqXU+KddMnSuQ9HxdeoZhSi8gHTbIj4H1v5Uy379///Q7Y4umCrT9XS7vgixdeMYv9GBZeqCQHgpaOUmPPcHx4q89e/ZsWZeu0rNC/HiyLENgFDkdcMABYVzygSxtzxJJjXTiw4KkOb9mNNaR8anXXnvt8Lx23333NCFUpT3qqKPCfcXzMOu+5WA///nPjfuX4VFqTTKkih5TWT5Q1zqnsr0nwwfpeRDMl23YK3EPYo+/upIn0pNMPDbT8hprrGHdYKLV56ffj0zxynqpCP7jH/9oSThHHnlkaCeNSz755JNUx2l2Yx1pkBO3SNNIJwh+k002CfeT5kPIwIEDw+1qVbbjQ+QEMUtvPPHekuReLg330kw77bRTGEewb3mVhhFZJn1f+nyWfbbztrqRPt/O52x7btL7mG5Sa/7UU0+13W1h6QYPHhw5H+ltk6l9BEzXZ/ucYXPPxGUv6nyN5zV1vmo76n3VJp26xuX7Xp55Is/dTBbx9ePGjcsztNTHkud/MkyMHrf8qMKVSXrErdW7ux637bz0eiPPmKWennZ67733KqNGjUr8Mek666xTeemll9LusrD0Jq/CAnL4wK5bUe9r/OKh3he169Q6n5Rxps4VyPv7/XaXllEdkv5uvvzyy+1+6k6fX9vf5fIsyPJFX9JFHqzL45cav/rVr2rGcPXVV7fkgpShS4Lz1F+HDRvWkuPZ7lSGhNLjOe2002w39YeSkR5f9O3rDdNks/OsjXXijVeuv/56m8Ma0ySNTRicszRUyjJJbxvxhwrBvuVVzqXWpA8jt/zyy1fkIQVTvgIbb7xxpAxIvpVx2CtR0689fT5fUfPRpMc1Pa5a8xdffLF5Rzm+Iw22asWpvyfDXbVqWm211cI4hg8f3tBhmtVYR7r71s9b5htppCMnIUNI6vuy6Y1IhhHTt7nhhhsSPeR+KkNS6GlN840+DK7VUFO6iG50MsXZ6P7afTu8zDks3buafOLrH374YfOOHHhHfs0sdSU97jT1XgdOgRDqCOh5q8/X2axj39aN9HkXQKjzNZ4L1PmidtT7oh6dvqTf6/T5TnPZZ599IvUh3UKflwYhWT6T5OH69NNPV53LxIkT8zh0zWMEvehILzi6adK8/Ggy/mw1KV18nfTsLF9Ky7OPYGhmU1DSY8mxxx5bkR7H4/uR5V122aXy4YcfmjZ3cn3Secg6pmoB162o91Xnme0a6n0LpDq5zse9b8F10IlzeX6/3wm+DzzwQGJd6bjjjuuE03f2HNu+hpdnQZZhSEyVQ1mfxy81kj7E6TFtvfXWLbsY5dcJ+rFkfplllsk0LFPWYOWLSL1XAGk0YjPucVJPOo1+UZl0Do021pEPwxtssEHoLEOOpe0lSI9n9uzZicMaBfmY9dcmtRqvSey1HopId8X6h3n5wpcpXwHpPaNLly7h9RZcF9ILUxmnIP74qyvncvDBB1dZx2MNlm0abORxXnfccYd1zHLfa8U0efLkSAz33HNPw4fJ2lhHhtwK8ih4bbSRjpzEiy++GNmfNNypN5144onhNjJ8oWloRNtfdR1yyCH1Dml8/5RTTgljCTyC1xdeeMG4Xb03gn3EX+tt16nvx52C5U710M977733Nl6jgZO8So9gc+fO1Td1bj7+4E7injBhgnNxElDjAvo1qc83vsf23lI30uddOGvqfI3lAnW+ajfqfdUmnbxGv9fp851mIsMt6+dvmt9yyy2dp4n31CpDF8+fP7/QuN98801jLzoLL7xw5Qc/+IE/FJb8MjuIVXq8lR7X5YeGxxxzTMU2j/S8kx7spTGO/DDmoosu8oe2kkZZ8kMyPZ0+L8PAuvIjp7SZpp+HPp92P52QXvfR5105d+p9jeUE9b6oWyfX+aRcM3WuQJ7f73eCsnxfnlQP69GjR+qe9DvBK69zbPu7XF4Fedq0aTUbPMiv1tMOxdHIRSANOWTYD71iqs9LwwfpmrQVk6k3n9tuu60Vh7Pe55VXXhnxOOuss2pum9RI5/TTT6+5TSNvNtJYJ97wJWtcf/nLXyI2+rWSdWgSMTn88MON+99vv/1qsh1//PGRbZ999tma6Xmz+QJXXHFFJA+C60O6Ey7jFMQff3XlXGyHkJLGeq5M0ntN3NO0PH369JaELT2dBceUv7Uff/xxpuM02lgn3vuNxJSlkU5wEjJsZXB+Q4YMCVYbX/XGqfvvv78xXXxs6+AY+utmm21mbOhj3LH2Rq2hFR988EEtZbpZPUZ9Pt1eOie1bqTPd46A+UxrPdjXrQYMGGDeiSPvXHLJJeG9QmKXL3JMDfUcCZkwUgro16Q+n3I3HZNcN9LnXQCgztdYLlDnq3aj3ldt0slr9HudPt9JJlOmTInUh3SH+PxJJ53kPM2PfvSjyPlIr9NFTv/3f/+X2Gu2fA6X4arE32aSL4nuv//+yh577GHdy2s8/+oty3MT6WmnrJPp/Mp6Pq2M23Ur6n2N5T71vqhbJ9f5pIwzda5AXt/vd5Kw3vBP/xsq3xUzFSPQ9ne5vApy0nH0i7xfv3655fBee+0V+SCnxyHzreoGXxorJfW+seOOO+Z27kkHkl9Ar7jiiqHJcsstV3n//feTkiYOd3Xqqacmpm3GyjSNdeSXKBtttFF4HnJOc+bMyRTGyJEjw/3FrxP5ZUrWaddddzXuXz7gmyb5Ql96YwpiKsMXZKZzKfP6TTbZJMyDIC+kxW1Zp+Ac4q8unI/cP+NxmZaPOOIIF0L2Y9DvSaZ4ZX2vXr1aFvPOO+8c2jWr17i0jXXkF33x829GIx1Bkweewb6l57paU7wHnlrDC0qXlsF+k16lN56pU6fWOlzd92S4s6R9y7rHHnus7vamBKZ9mtJ3+nq8kq+A1157zXh9xs2kdyjXp9133z1yPjJUAFN7CcSvy2C5vc6yeWcT+MRfm3eExvZEna8xN9mKOl/Ujnpf1IMl94d6ziOPrr766kh9KP43QF9+6KGH8gip4WNID8ff+ta3IufTzJ6+0wYmP86U4ah0Qxk+7NBDD61k6fFXPnPKj/yk9xt9343OL7XUUv4PZoLefNKepyvpTefvSnwuxeGyFfW+xq8U6n0L7Dq9zidlnKlzBZK+d+/Tp0/ngjThzOV5qD6SSfB3dNCgQU3YO7toRKDt73J5FeTevXvX/EAh3XPmNckHt6BwJb2uvvrqFel5pxXTD3/4w6pjywc5GWKjyOnmm2+OxLXTTjtVGST1pJPHFzO2jXWGDRsWOYfLLrssM6n0lpB0jcg6ecCRddphhx2M+681ZJd0lavH9fjjj2cNhe1TCpiGvTr66KNT7smd5Po1pc+7EGH8HqXHF5+XRiQuTDNnzkys1MXjleVWDl2nNxaSX9w0a7JtrCNdacfPuVmNdORcpFe6YP/y97RWA009FklrapQq++3fv3+432D/+uvtt98uyTJN+nji+r5lXrpCb3SK7ytYbnR/7b5d4BN/bffzrnd+V111Vc0yoHuNHz++3u4KfV/q9dIQXY85a6+LhZ4QB08U0PNXn09MzMpIeXDJizpf4xcndb6oHfW+qAdLNNSRa2Do0KHG+7/+t0AamNQait2F62nSpElV5zJx4sRCQpNncrqfzMvzxCyf6eInMmPGDH9oK/nBSPxYNsuSp4cddlilrD1Axz1M5xxPx7Lb9z7qfY1fodT7Fth1ep1P7odMnSuQ1/f7nSYsHSPE6xpSl2qXelTZ8rPt73J5FGTpSjN+UceXr7vuutyujRtuuKFuPK36cHfnnXcmHvvMM8/M7fxNB4r3NKT/EiWpkc7JJ59s2lXT19drrCO9IujXlHR3+Pnnn2eK46OPPkrsASk4jrSszDrJsCvB/vRXGZ7NNImFnlZ6ZGDKX8D0BWatL/7zjzLdEfXrSp9Pt5fWpD7kkEMi170enz4vrZ2lgYwL01133WUVs8R/6623tizk5ZdfPozjD3/4Q1OPU6+xTnyoGTnXZjbSkZN55plnwvOT/T/11FPGcxw8eHCYVh6cmiYZilO6J9evLX1+t912M21qvV7uFUmt8+U4Cy+8cKYhefRY9Xnr4DosoW6kz3cYQ9Xp7r333sYyoDstuuiiFemd0eVp8uTJVefyyCOPuBwysTUgoF+X+nwDu+qITXQjfb7ok6fO13gOUOeL2lHvi3qw5PaX1Xnlz6qrrlpVJ9L/BgTzW265ZV4hNXycc889N3Iuiy22WKWoXmI+++yzylZbbeXHI5/lpEF41meSJhipd8szdOmZ3vR5MshHee3bt2/l0ksvdeY5iem80q7Xz1GfT7ufTkiv++jzLpw79b7Gc4F63wK7Tq/zSblm6lyBPL7f70Tda6+9NlLPDP5+XnjhhZ3IUfg5t/1dLo+CLL3lBBey6XXcuHG5ZbYMJ2GKI1gvXZO2YpIPjXpFKjieNCwpepIeXHr27BnaSG8DY8eOTRzuqoixqk2NdV566aVK9+7dw7jF9O67787Med9990X2GeSVvPbo0SPz/mUH0kBL328wv/HGGyfuf8KECZUlllgi3EZ+HS7DYDHlLyBdCAb5FbxK+SnzFJxH/NWFc7Ids1p6b3NlOuqoo6qukbhtsCy/jmvFJA8M9Yd3rWiEamqso/+iJTjPZjfSETO5Bwb7l1f5u2WapIvKIO3o0aNNySoPPvhgmC5IH7zKEJbN+GWk3hNQsO/gdcMNNzTGZvNGsJ/4q822nZgm7hQsd6KFfs4ylGNgUeu1WUPq6cdu9nx8+L1u3bplagzX7PjYX3METNdpc/befntx1Ys6X2PXGnW+ajfqfdUmnb7G1fteXvkiwy+ZDOLrTzzxxLzCavg48Z6m/+d//qfhfTVjw3feeaciP8aTnn7ymmbPnl15+OGH/R/DyLGHDBlSGTFiREXqvvfcc09lypQpeYWS+3Hi12ywnHsgJThgYBN/dSF06n2N5QL1vqhbp9f5pGwzda5AHt/vd6Ku9Nivfw8b/A116bunTsqXtr/L5VGQpdFBcCGbXl955ZXcrqu33367bjxZvySrdTJHHnlk4vFb8QVqrTiS3pOhC/QvdZPyq8gP7EmNdeIxNiu+448/PjGf5Hh77rlnEl/qdW+++WbVGNay/2WWWabqC6Tzzz/f72VBP99mNEhKHTQbVEzDXh1zzDGl1tGvLX2+6JOKN8TQY4vPy0MpV6akxlzxeGW5V69eLQtZxrPXj9mqv7VJjXX048p8KxrpCJz8UlH/u1Wr16BXX33VH2ZMhqiTh5qmadSoURE3/Vy23XZb02ap1h944IHGYxx00EGp9hVPrMerz8fTsfy1gG6kz3eyz+uvv268PnUjmc9jGNSseSG9YOlxDxw4MOsu2d5BAT2P9XkHQ3UiJN1Iny8yOOp8jetT56u2o95XbdLpa/R7nT7fKS7SC4t+3rXma/34wQUveSaz5JJLRs6nmcM8u3COxFBbwHT91t6qM9911Yp6X+PXI/W+qF2n1/mkjDN1rkAe3+93qq7p2X2t3vw71arV5932d7lWF+R58+bVHD4iqCzKMBN5TV999VVFuukPjp30Kr+Yl1ZzrZiee+65xGMfcMABrTjc/2fvykO9Kr44/tH2kPKhkUgYpqG4BEZqqBWJJoUiLqiJ/pFhvVa3CklNfbmVROQK4oYLirmSkokJ9TRFRM2lxA0k4lFooeYzN+7v91Hmee7cmfu929x7v3PP+Wdm7nfmzDmfWb7n+51z54TmCWcDFSZ49sknn4Tml3QDP2edfv36ORjfJEh+O4digrBHSREcCyhvkX/llVccxOqdNWtW/RW64jMcSuO2CqZsEJDDj4lxKeewV0BS6CGn2aB8r9cwMas3b958r2GGOTiB4FYyGUtVuaqqypik+/btc8mAm9NMkZ+zjiknHaELvakuif25S5cuLtzouC1cuFB0Gytt3ry5to/169fH4k3lpflYTC1uTDGieYtVLqma7nuO4iPyad6KWVJwRYXbt2/fcYAW8iJFOAIm+xCgY0zz9mmajEYUI5pPhns0LmzzRcMNrdjmi44d233RsSu3lnSvo/ly0yOqvKNGjdL+/qB43H///U6a/9FG0Wf//v0eXWpqaqKw4jZligCdszRfpuoYFZviQ/NGOw3AnO2+ACBpqrDdpwGmxGNbbT6sa6biImD6fL+4yDrO3r17PfYm1tt7771XZFgy0d36Xc70Qj5w4IByMlPDsFGjRqkPbpDr/E3ecIMYwRQD5BG+6cqVK6ljIXcI5yrVLUh9+vSRq2ZWRsgSGb/27dsnit9rr73m6QN9It70H3/8kajuH3zwgbIvWUeUcfi/dOnSRPtnZuEQUK3fcg97BQRU8w3PsqagMauxNv7++++sxb3T/7Zt27R4yjivW7fOmMw7duxwyZGUI6NO4L59+7r6g66tW7fWVU/s+ZNPPlnfL0JKxaFLly45cNaVx0mUz507F4f9nba42Ujwk1P0HXceyzxFObbgljIQ+MippeoGUmv48OHaOUpxguN7XV1dIJ5ZVTpy5IhHlx9//DErcbhfgwjQuUnzBrssa9YUI5rPUim2+aKjzzZfNOzY7ouGW7m2onsdzZerPmHlxn9mVG9dvlu3bmFZp17/ww8/dOlSUVHhXL9+PXU5uMPsENDN3+wkym/PecWK7b7oc4btvvDY2WzzYY0zFRcB0+f7xUX2ruY415C/R1XRUIqOk2n9rd/lTC/kRYsWeSayPLFbtWplehw9/Nu1a1dSLpM3ACxYsEDZ/7JlyzyyZvEAN4N07drVJeNDDz3kLF68OAtxXH3iajE4RdB51LhxYyeJw1PaEQ7PaR/I4wA17iEw7YPmJ02a5ODNJblPWkbM7UOHDtFmnE8ZATg6qA7x8UdRuROdazSftV4qg4jKJ/JwMMwLffTRR75rWciMtLa21pjYeKuQ9mXy1id8r9EQVLTfsWPHGtMRjPEdIPpbs2ZNrL4QUlDwktMWLVrE4i0af/3119o+nnvuOVEtcirLLcqRGVreUOAjp5ar7ateEId24PX888/78snDh1999ZVrvcGehVM6k30IyGtYlO3TNBmNBD5ymgz3aFzY5ouGG1qxzRcNO7b7ouFWrq3k/U6Uy1WfMHJfvnw58I2vebhJ2083/Ccj306K27WZioWAWL9yWiwUgmkrYyTKwVqbq8V2X3Rs2e4Lj53NNh/WNFNxETB9vl9cZO9qPnv2bNd/iuI71NQZcdHx1ulv/S5neiHr4riJCY20Y8eOOvyNPccbIlQGVX7o0KHG+sfb8g8++KBHhu7duxvrMyzja9euOf379/fIOGTIEAdeyFkQHJlwwELHCzcpHD9+3Ig4iOHdq1cvp0OHDg5uvcHVkibpzz//dD7//HNn0KBBDm5tgUPZgAEDnKlTpzp5Dy1hEpc88V6+fLlr/om5ePHixTyJGUkWoYucRmKWUKMwMavHjBmTUK/x2XTu3Fk5T2Rs27RpE78zHw7Hjh1zyXHixAmf2tE/8nPSETqbcta5ceOGy0Fo9+7d0RX5f0u/G85GjhwZi7doDOcGgYucTpkyRVSLnMo8RTkyQ8sbCnzk1HK1teqdOXNGOz9ljCZPnqzlk5cPcHBD5e7Ro0deRGM5EkaAjjPNJ9yNNewoRjSflYJs88VDnm2+aPix3RcNt3JtRfc6mi9XfcLILYdJofrL+W+//TYM69Tr/vzzzy7bDvIjhA5TsRCQ560oFwuFYNoKbOQ0WGsztdjui4cr233h8bPZ5sPaZiouAqbP94uL7F3NEVlF9dJ+7969iw5Nqvpbv8uZXsiqEEqyYfjCCy+kOqjo7NVXX/X8sJPlatmypVG5dKGVTp06ZbTfMMxv3759J+aeCpuDBw+GYRWrLg6Nevbs6RmzF1980TF5Q0QsobmxlQh06tTJMw/xNpcNJK9zUc5St7Vr13rwFnLJ6ZYtW7IUtb5vhDBEiDxZPlW5qqqqvp2JzO+//+6SI64Ti0pGlZMObIslS5a4HGigvwlnHRjMFNuTJ0+qxAz8zO/GPegUlyAvwrRRmWkeIUPjEuVH83H52tqeYkTztupbSi/Mc4qDXz7vTsSwYysrK136VFdXl4KAPy9TBHRztUzVMS523vBimy/ekLPNFw0/tvui4VaurfK276WJ4+rVq132kA4LPMcLZHmm0aNHu3TBy3z4Dc5ULAR0c7hYKATTNo9Ysd0XbOx0tdju0yGjf26zzYc1zlRcBEyf7xcX2Xua9+nTx2V7Ys3hv33sxUzpIGD9LmdyId+8edO57777PJNYNhAx0dMmnZOMLNu///5rTLSdO3cqscnjNbNffPGF58AVm9HAgQMdvM1iin777TfnnXfe8dyig3EaNWqUg5sUmBiBtBDAFcsqBwyEObKB5P1PlLPU7a233lLuk0I2kWI/wk1leaDvv/8+kMyQHSH2TNLVq1ddezf+DEmSVE46c+bMqe8iDWcdhAMU8wAprnWPSn/99ZcLL8oX+SQcaf3CXiUVWkuWW5Sj4mJ7O4GPnNqut06/4cOHu9aUjIsoI1xnXV2djk0unsv7A2T/6aefciEbC5E8AmJuymnyPdnBUcZJlLPSjm2+eMizzRceP7b7wmNW7i3EPien5a5XEPnnzp0byL7L+0tIcMJu1qyZSxfcSM1UPATkdSzKxUOitMYCGzkt3dJcDbb74mHLdl84/Gy3+bC2mYqLgMnz/eKi6tZ848aNLttTfJ/OmDHDXZFLxhCwfpczuZCDXmMIp5m0CbcYiAXll54+fdqYaPiBKcdVhiyPP/64g8/yRuvXr3ceffRRJW5du3Z1Nm3alIjccIbYtm2b8/LLLysPTCsqKhz8ycDECKSNwIoVK5TzPy8OInHx0O2FcfnGaR80ZnUWIRR1esHZUoel/Ly2tlbHJrHnCA8o+p00aVJifFVOOnDqlMm0s87KlSvr9WvYsKHcfaiyzvAGfk2bNg3FS1fZL/TmhAkTdM1CPRfjLaehmBSosoyTKBcIApeqsEMFBn5pnsK1uhQghS+//NKlC964vn79OqnBWZsQ0M1Xm3RMUpe84cU2X/zRZZsvHIZs94XDy4baedv30sQUIdZ1+tPnCBmaZ9q6datHj2+++SbPIrNshhCg85bmDXVX1mwpPjSfpVJs98VHn+2+4BjabvNhXTMVFwGT5/vFRdWtOf5HVJ2LP/XUU+6KXDKGgPW7nMmFfPjwYc8PKGoQivwbb7xhbAB1jMeMGRNItpqaGh2LRJ5PnjxZKcd3332XCP+kmfzzzz/O+++/r4zLh/GE49Hrr7/uLF++3Dl79mzg7uHUBaNp/PjxTqtWrZSYIBYgbtFBXSZGIAsEOnfu7JmbeX/jLAxOYk+W0zA8kqwb1NkT8poIqRRVFz9HDIptmzZtonYRqt2AAQPq5y1CtyVBKicd/PmrI5POOvT2D/zZE4fw/UbHiOYHDx4ch/WdtrgSs0GDBto+jhw5ErsPMKBy03wizC1kQjGieQtVLakSbDeKgV8+Sce/koJFrNC3b1+XPj169IjIiZuVAwK6+VoOsmchY57wYpsvmRnANl84HNnuC4eXDbXztO+ljee0adNcNpEOi3HjxqUtWuD+8EJjhw4dXHo8/PDDub/hMbCCXDEUAro5HIpJQSrnDSu2+5KZeGz3BcfRdpsPa5ypuAiYPN8vLqpezXX+BHxrtxcrE0+s3+VMLuQdO3a4fkDpDMM333zTxNj58vz4448DybZhwwZfPnE/xIGI6tAuiQPBuLL5tT969KjTs2fPkhjirWyENoPzDsIDzZ4928HbzXBQevfddx1cUfvEE0+U5IODlhMnTviJxJ8xAkYR0IW9wl5iC+n26Kz0CxOzGm/W5YFw/SzCweiwpM9xs1saVF1dXS8PQoRduHAhVrcqJx3s7aXIhLMO1uVjjz1Wr19ce+Lpp5+u50XHCnmErIpLwEnmK8pJOm4JnnIaV35b28s4ibKt+vrptXTpUu0cFbiIdNeuXX6sMv/s1q1bziOPPOLSB/shk70IiLkpp/ZqHE8zGSdRjsc1Wmu2+aLhJrdim09GxL/Mdp8/PjZ+KvY5ObVRV1mn6dOnu2wiGQNRnj9/vtw0N+VVq1Z5dJg6dWpu5GNB0kVAzFk5TVeK8uhNxkiUs5Ke7b5kkGe7LziOttt8WNNMxUXA5Pl+cVH1av7LL7947FCsPZx7M5lHwPpdzuRCpuEohBGoSt9++23zIyn1MHHiROXCkuVL40fqSy+95JHlgQcecC5evChJnb/ir7/+6sCbsLKy0qODjGXYcqNGjZxhw4Y57JWYv3EvokS6/cyWsFcYU90azWq8w8Ssxm1feaAffvhBi6OM77p161IReffu3S6Z4vSrctKZOXNmYD2SdtaRjeTt27cHlkWuiO9cleOsGDfcEhiX2rZt6xoLwRvpZ5995st+9erVd94g7dWrl/Pff//51qV8ad63UYE/pBjRfBEhGTFihHaOUmzgkFhXV5driA4ePOjRhW3KXA9ZbOHoHKX52IwtZUAxovks1GWbLxnU2eYLjiPbfcGxsqkm3eto3iYddbrgv02qsy6flxdgZD1u3LjhtGjRwqVDkyZNnMuXL8tVuVwQBHRzuCDqh1Izb1ix3Rdq+LSV2e7TQuP6oAg2H9Y4U3ERMHm+X1xU1Zo/++yzLlsUa69hw4bOlStX1A34aWIIWL/LmVzIc+bM8UxclXGIm1XSpqDXvqZxrb/OAWDevHlpwxK5PxzW4O0WHPDIP55VY657hht4MB927tzp4Ic4EyOQFwS6dOni2c9wG5RNpFuXWemIG0Z0MtHnzzzzTFYievr99NNPA8kM+Wtraz3tTTy4efOm07hx43q5Ro4cGakblZPOjBkzQvNK0lmH2hkwjEs5sPgJu2XLlnqM6PxCHvjh9p44dODAAS1/OAidP39eyx564Y9oIdemTZu0dfGBqCenvo0K/KGMkygXEZIgtxwCn+7du+ceHro/QOaKigoHcaWZ7EVArF05tVfjeJrJOIlyPK7RWrPNFw03uRXbfDIi+jLbfXpsbP5E7HNyarPOQjc4/ct6q8p79uwRTXKVqhyNcFs3U3ERUM1fPGPyIpA3rNju845RlCds9wVDrQg2H+99weaCrbVMnu/billUvXA2ovpOXbZsWVSW3C4gAv8DAAD//5tcc08AAEAASURBVOydCfwV0/vHnx8tKkqU9sVSEiWJX7IrkVBEIRGKiEpSKW0klL+UJVuIKCQqKipJCBWyhaRFKZQiLSruf57rN7dZzrn3zJ3t3Hs/5/X6vmbmzDPnPOf9zDPf5545cw4l8jzdd999CSKy/TVs2DCQVvfq1ctWrrMe87hbt26B1OelkGHDhinp1qlTJy/FZiW7devWROnSpV36HHPMMVmVp8NFa9asSUycODFx++23J7p06ZK46KKLEqeddlqiXr16ifr16yeaN2+e6NixY6Jfv36JBx98MPHKK68kPvvsMx1Uhw4g4CLwzz//JIoUKeLy0T59+rhkcznDfCY7t3G0ad26dS7eTr3M4549e8ahorDOU089VUnvOnXqCK8PK/Oqq65K6cX/bzZt2uSpqocffjjxn//8J1UGsx86dKinMqzCTz75pKu8m2++2SqScf/vv/9O1K5dO6VTmzZtMl6TToDrN+8p59Zv2Vwv/y90lmseN2vWLJ1qiQkTJtiu/fjjj9PKm+U6t2kvKuCTTk7mcaEhWblype0+MzmItv3799ceT8uWLW3tadq0qfY6Q0F/BET3KuchiQnowgsxn9g+2eYi5lMjh7hPjVO+Seny3IuD6/Tp021xkYxFpt8Zcej+008/JcqXL2/Tv2rVqont27fHoU5kdf7555+JDz/8MPlbkPvux44dm3j77bcTK1asSHAfVaEn2T1c6FxE7deJFeI+kYWyz0Pcl5ldIcR87ONIhUsgzPf7hUtV3PLffvstsc8++9hiUva/k046SXwBcgMjkPdPuTAd+eqrr3bdtKLg0OvLuSCsO2LECCXdLrzwwiCqy1jGtddeK9QHg1cyooMACIRO4LnnnhP6p9fBDqEr6rMC0fM5rmCfB/rJ9HHmT5061WfLg7l8x44dwmDNqS8f86CNKNMbb7xh4zl48GDl6kWDdO68807l62WCfgfrOAevPPvss7KqlPJ5kLLIVpzHDPwkvjfKli0rLZ/bki6dccYZqWu5k5oHKaVLsnaku6aQz4HXv9YfN25c6j6TMTHzZ82apfUts3v3btcg+CCeW1o3GspJ71+gERMw/dm5FUuHl4uYL1i2iPnUeCLuU+OUb1LO5515nG/tFLVn9erV0v+TJgfezpw5U3R5bHn8u+f000936f7444/HplPYFfPgef4YqUyZMq52m7aqW7dugn9P8+/MQk0mC+e2UHmka7eTkXmc7pqwziHuC5Ys4r7MPAsh5mOfRipcAmG+34+LKvfp7dq1K67q09Z76aWXCuOz7777Lu11OOmPQN4/5cJ05Msvv1x405oBobm95ZZb/Fkpi6v/7//+T0m3c889N4vSvV+yYMECoT7du3f3XhiuAAEQCJRA48aNXf5Zo0aNQOvQoTDzmezcxqFbutlHrPrttddeic2bN8ehoqvOefPmue4Tq67Wfe6ciDJxB2etWrVS+vGgkT/++COjCqJBOnfccUfG61QFsh2sw18QHnXUUan27Lfffp5nCbLqyPcQ30tWG1n3ly5dahX3vD958mRp2az7tm3bpGV+//33ttmHVAZ5WXW37ksrKfATVkbW/ULD0rlzZ+l9auVSrFixBM8GqXPir4+tOvP+/PnzdVYZugVAwGlz8ziAovOyCJOPcxt1YxHzBUscMV9mnoj7MjPKVwnn8848ztf2OtvlnJXGbL91yx8p6ZQGDRrkiul4FttMHy7o1AZVXXbu3Jno0aNHYu+993a12Woj637NmjUTPLCnEJOVg3W/EFlkarOVj3U/03VhnEfcFyxVxH3peRZKzMd+jVS4BMJ8vx821U8++STB7xl4wo8WLVokjj766MRBBx2U6qMvVapUokqVKonjjjsucf311yeeeuqpxIYNG8JWK235b731ljBO45VjkMIjkPdPuTAduW3btsKb1hoU8n7v3r3Ds6Ck5Pvvv19JN16iKap0xBFHuHQqV65c4q+//opKBdQDAiAgICBa9qpv374CydzOcj6bzeM4WsVLQ5n1p9see+yxcagnrJMDy3S6Ws/xdL9Rp8cee8ymHy8BmS6JBukMGTIk3SVZnctmsI5z4ItfvV5//XUbG6utKleunFW7rBd17dpVWv6VV15pFXXt33bbbbZrVWbas+pv3XcVjowkASsj636h4bEOfrNycO6feOKJ2qNxLr9bsmRJxNPaW82/gs571Tz2X3J+lmDycW6jbi1ivuCJI+ZLzxRxX3o++XzW+bwzj/O5zda2nX322bbfFWb7rVv+qFGXNGfOnNSLGlPHAw88MLFmzRpdVAxMD17m6pRTThHa59BDD0107Ngx0b59+0SDBg1cMocddliClwcrtGTeE85toXFQaa+TkXmscm3QMoj7giaaSCDukzMtlJiPfRqpcAmE+X4/DKqLFi1K9OnTJ8Hxjfn/yMuWB+/wzINr164NQ72MZfIAyerVq7t052VZ83EgeUYgEQnk/VMuTEe+4IILXDesyOn4JVTUaeTIkUq6nXbaaZGpNnz4cKFOkyZNikwHVAQCVgIif0UeCf00n7lY74ko9r2sWR3HjGwyBk2bNlW6N7hjIo60ffv2RIUKFVI68kBQ2Sh00SAd/poxrORlsA4PXq1fv36qHdwm7tj0k5wv9a3+zLMD+k2tWrVK6Wstm/fffPNNafHc4XrAAQekruWvR1WSsw4cZ/fcVmGdLzI8w1a6WaWs95DuX4nwjFvOH83sg0j5T8B6n2I/u+cec4syIeYLhzZivvRcEfdl/3zI12dr+jsmf87yUsGZbMgfXOqQfvzxx0TFihVd+uqy7HWQjHhph3POOcfVVrYVv8iyLm/18ccf22ZbNe1ZiLOxm23HNvtnepD3sUpZiPtUKHmXQdwnZ4aYL/vnQz4/W+V3TG6eCfP9fpBEVq1alWjdurUw3snmfitevHjiuuuui2XAzoABA4TtmDFjRpDIUJaFQLQ9VZaKo9oN05FbtmwpvGGdjte/f/+ompuq54EHHlDSLcqvhjlgFc3cwRyRQCAOAk5fxXFhBrhR33te1qyeNm1a1OoJ6+NpqnnGBhUfUVm6SFhJAJkvvPCCTUf+qpJfaluTaJDOwIEDrSKh7KsO1rnxxhttbXjkkUd868NTaMpsN3bsWN/l8+x8svI3bdokLd8ZR73//vtSWesJWV3I9/YMtzLN933ZEqyie0aX567MJh988IHL3/jZh5T/BET3K/K8PfeYV5QJMV94tBHzydki7vP+XMj3Z6n8bsmvM/zBg/XDDZFdecYa5+/DqCmsXr1a+JV1t27dolYlkvpkM/PyrKzW9M477yR42WSR3erVq2cVLYh9EQfkeXu+R32jIO4LjzjiPjFbxHzengmF8gwV3y25mxvm+/0gqPA7k3vvvTfBM+HI7rG6desmbr311uTSVm+88UZi4cKFiU8//TQxe/bsxNNPP5246qqrErzcp+h6nsnmyy+/DEJV5TKWL18uHDity4B35YbkkGC0PVUxgAnTkdO9mLI6VRQvAJ1oVQfq8D/0KNP555/veuDw+sSFOI1plNxRl5iA1U+xX7jBrfjuCC9Xdc1qfjbyesM6JB5Aoeoj3DkRZ7r00kttunLHoJlEg3R4lHhUKdNgnQkTJth0r1WrVoK/QPSTeCYRvpdk9lu2bJmf4pPX8lTlovJ53V1ZYhbWa/irA9VkvQ772T+7VXnng9z48eNt91u6++bnn3/Wusn8RbFV/xIlSiS2bNmitc5QLhgCVrtjPzeefYj5grn3ZaUg5nOTQdyX/bMhn5+r7jslf3O4/zWTLXlJgrjSypUrEwcffLBLx4YNG9pmlolLv6Dr/fbbbxP8RbjTJjygyvo7lz/s5JjWKWc9TvcBSNB661Cete3Yz+7ZHrUdEfeFSxxxn50vYr7snguF8Dy13ym5fxTm+32/dLZu3Zo488wzhfFLsWLFErxSwg8//KBczWeffZZo1qyZq7yyZcsmePBMlOn000936cEx3caNG6NUo2DqwkAdH6bmZaNUHu5hLqchU//+++9X0o3X/40yvfrqq0K97rnnnijVQF0gkCSg4r+Qyf/AN2p3OOKII4TPQee91qhRo6hVk9Y3bNgwJZ25DdzJFmfiDrxq1aql9OXlbmbNmpUQDdK5/fbbI1dVNlhn6dKliX333TelN7MMYurz6dOn28q03meVKlUKpP133XWXsA5ZjOH8WpKXKfMyYNfaBuxn/4wOxPg5Usjo0aOF96jz/uElpXROvB505cqVbW256KKLdFYZugVIwHm/4ji751+AJslYFGK+jIh8CSDmc+ND3JfdcyHfn6fuOyV/c/g3RdGiRW2xktO+V155ZSwAVqxYIfxampeOXr9+fSw6hV0px6lO/nzcuXNnW9Xjxo0TypnX/uc//ym4gelm27HN/rluu8kiOEDcFy5kxH12voj5sn825Ptz1X6n5P6RrgN1+IM52fgAHrzjZ2DNlClTElWqVLHFRieccEJi9+7dkRlUtqTsgw8+GJkOhVQRBur4sPbJJ59scxbZQz6OgTojRoxQ0q1p06Y+CHi/lKcC4y/snawOP/xw74XhChDwScB5H+K4MINcn7eRp8u5A071PuO1hnVJZ511lpLe3MmoQ3r77beFUzRa2cexLKXJRjRYx6ob7wel32233Sa13SWXXGKq5GvLnc48IMrZhgMOOMD1ZSgPJHYug+l1QJKzHhxn9+z2ZfQcu5inoVW5T1q1aqV1y/jHurMdL7/8stY6Q7ngCDhtj2O9n32I+YK799OVhJjPTgdxX3bPhXx/ntrvkvw/uuyyy1zxktXGPNtoELOKeiH50Ucf2T4mMfXhGVS9fLDgpc64ZXmJL9nMri+++KJNPV7ywWQi2tauXdsmXwgHIg7I8/aMj/I+QdwXDW3EfXs4I+bz9jwopOfnnrskP/Z0HKjDy62edNJJwtiFZ523zhqYrRV4dQNnHBXlsvc8W1Dp0qVdbTzmmGOybRKuS0MAA3XSwMl0SjT9k+ihH8fSVzxDjUgXZ57sa/dMbfdznqf8curBx/zwQQKBKAmI7kPkFV6gG+U9xx1SqvfY66+/HqVq0ro4uJStFe9sC0/1q0uS/a9hnfv16xe7mukG6/BggX/++ScQHVu2bCm955544olA6uBCnMvxmPdGixYtEvxD4u677044Bzjzl5E804nXZJaNrb/ntVfuuSw/ZMgQqR9Y76OePXtq20yeTadevXq2dvCP5m3btmmrs1MxbgMvLbZ9+3bnKRwrELDeq9jP/vmngDoQEcR8gWBUKgQx3x5MiPuyfzbk83N1zx1SGHtffPFFxmWULrzwwkhgcOzDv4OcHyrw/XbooYcm1qxZE4kecVSS7iWycxmIm2++2RbjOv1Rh9/vUTN0MsCx9+d7lDZD3BcdbcR9/7JGzOf9mVAoz9HovDGamnQcqMNxieh+atOmTaBQ+vTpY6vnjDPOCLT8TIVde+21tvrNNvMSXUjBEvgPF2cAztv0f//3f2TMSmBrn7H2Ly1evNiWl82BMcMAvfXWWxkvHTBgAN1xxx0Z5YIUMJYpIeNr/IxFHnfccfTxxx9nlAtS4MsvvyTjRYOryE6dOpHx0tCVjwwQAIHgCRg/IsmYTcNV8ObNm6lMmTKu/HzIMAYFCJsR5b/BG264gcaMGSPUw5lZt25dLWxhjBKnTz75xKme8HjixInUrl074bmoM1nvxo0bkxE82qo+99xzadq0aba8uA6MJaPIWH7LVv1RRx1FCxYsIGMZLFt+tgfGF6U0YcIE1+VGZzGtWrWKjGV0XOeyzTAG65Ax8EbpcmMGnuT//KuvvlpJ3iqkgy9b9dF9H7yIRL4msttDDz1EXbt2FZ2KPW/8+PHUoUMHmx6DBw8mY+ZOW55OB59++ik9//zz9NVXX5HxQoZWrlxJxuyaSRXLly9Pxpc4xM8o/r+xzz776KS6lrrAl72ZJW5eiPm82cuPNGK+PfQQ9+1hUYh7cT/3dGL+0ksvJfs70v3WN2ZcpN69e4emtjFTTjJ2M2aAcNVRs2ZNmjdvHhnLrrrO5UOG8dFJsm1r1651NcdY9ph+/fVXWz73rXMfuyhxvwj34RdarAh/Ft0N4jwdWCHuE9smjFzEff9SLaSYj1uc7v95GPcZytSHQJjv97NppTFLIp144olkDMa2Xc4x3ZIlS2j//fe35Wdz8Morr9Djjz9OHEMay12lijCWd6UdO3YQ96lHkT788EMyltxyVcX9/w888IArHxk+CBgPubxOYY64M172CUeUGeaw5Rsv4SJnbAwMsung1Mk8Nh4qkevGFR5//PEu/XjGBp5SCwkEQCB8Auz75nPA3BqdReFXHGMNZjud2yhVUl2z2qljrhyvW7cuSpwZ69qwYUOiSZMmtnu9RIkSCSPYzXht2AJGZ6Nr+vMDDzww4fy60K8exuApW/v5XuKpM/mLrzASxzzFihVz1Wm9h3nZTWPwV9bVW8uy7mddYJ5faGVk3c/zZtuaZwzASXtPmlx4aSkdEy8de/DBB9vaYLzkSPzxxx/aqWsM+E0wb54O1+SaaWsMUEx8/fXXtrbw2tszZsxI8HK+Tz/9dMJ40WM7X4gHMo6FyEKlzXHzQsynYqXgZBDz/csScV9w91QulhT3c083ZsZg5rSxCC/dG8YSosZL5MTDDz+c4N92IpuccsopeR/XGB+eCNvOPM4++2zhrWK8iEuULFkydR3bp3379olNmzYJ5fM9U3TvcB6Sm4AOrBD3ue0SZg7ivkSikGI+PPvC9Cb9yw7z/b7X1vPs99x/Jfq/M3bsWK/FueS5H8z4oFVYvlnnjz/+6LouzAzR/zfuj+R4Fyk4Ankf4YXpyBdccEFapzGdx5jZJjiLKZbEy22Z9afbnnbaaYolBitmzCgh1G/cuHHBVoTSQAAEhASMEbguH4zjWSVULqRM2bMwpOpcxXpZs1qmq875derUcbVZhwxeYkX0/9qYwSHx+++/x6LiU0895ZqO/ZBDDkkYM86Fog//bz3zzDOTy+Z069YtwR2nYSZe2sb4QjVx0UUXJRo1apQ48sgjEzy9vDH7R2LOnDm+q5b5ge+C87QA8EokjNloXP/zRFzee+89Le8C0UAjfpmhWzK+Xk9UrFgxLWt+6SJiX6pUqYT5O4A7HpwDfXiZL+NrHt2aHKk+Im6chyQmECcvxHxim4Sdi5jvX8KI+8K+0/QtP87nno5U+GXKxRdfLIw7TFbGTBwJ/tCAl6jym3hg9aOPPur6GMNaFy8HxS9h8j3dc889Uu59+/aVNp8ZGl+qJ+bPn5/YsmWLVK4QTpj3jXNbCG332kYnI/PYaznZyiPuy5acv+sQ9yWSv58Loa+PfRqpcAmE+X7fK9U33nhDGN8YM0YnOIbxm9LFT+b/tqVLl/qtxtP1w4cPF7Z50qRJnsqBcHoCef+UC9OR+SWf6SDptsZUqumtEMJZfuGeTifzXPPmzUOoPXOR/EUEz2pg6mFu4xo4lFljSIBA/hCQrZ2s45f5QVI3nzPObZB1pCtLxt2pT64ed+nSJV3zYz3HHa833nij63/OoYcemli0aFFkun3//feJZs2aufQ49dRTE/xFEJIaAZmPqF1deFLglUhMnz7d5XciLsZysNrdIMayCQn+0W/Vt2rVqgnumNQlrV69OnHeeefZdLTqy4P1eFYcYwms5MspfvEya9as5BfVVjneN5bqSxhT6wrLuvzyy3Vpcix6OFmZx7EokwOVmnyc2yhUR8wXBWVxHYj5xFxyOdfpw+ZxLrcpLN1NNs5tWPXlQrk8a/d///tfYVxh5XTSSScljOUFsmqSsbRnYuTIkYkaNWpI6+Evj3mmwEJJrVu3lrIIa2bXfGNrvT+t+/nWziDaY+Vj3Q+ibJUyEPepUApHBnFfOFzjKtXqv879uHRCvfETCPP9vtfWnXHGGcL4hlfe8Zv4vVzx4sWF5Zv+wB++Rd0XyKsnFClSxKVXy5Yt/TYZ11sI/If3DUPnbQpzDbsOHTqQ8YVuRnY9evQg40dbRrkgBYyvNMgYgZexSOMhQtOmTcsoF4aA0dlOzz//vK1oXld22bJlZLw8teXjAARAIDgCJ598MhmzBtgKNJbUIGPJHVtevh3EvW616prVxrJBZCz1oQX+d999l3hdVJVkTLtKxgBWFdHYZJhrnz59eJBySgcjyCVjxh265ZZbhOuupgR97HzzzTf04IMPkvGimoyA2lZS586dyZganXidWSQ1AnH7spqW+kiBF5ExQwvxetGZ0syZM+mss87KJBbZeeNLcDIG99HcuXNtdfJa1fzs0CHxmtn8DDU6FVzqHHTQQWQsx0udOnUiY8k913nOMD4uoGHDhgnPOTONWXbIWDbPmV0wx/Blb6aOkxdiPm+2CkMaMV8YVOMpM05fjqfF2dcKVmJ2xtT8ZCyDlfyNzbFVumQM2KFLLrkkGX8dfvjhQtFt27aRMfg42Zc6depUWrJkiVDOzOTY8sknnyRjoLWZlffbatWq0Zo1a4Tt/O6776hWrVrCc8jcQwD+vIdFpr24WSHuy2Sh8M8j7gufcRQ1yHyZ67b240ahC+rQh0CY7/e9tHLVqlVUs2ZN4SXG6jY0ZMgQ4TnVTO73MwYCpRXnd+bGR8BpZcI42apVK+KY15q4j4/7WitVqmTNxn62BHigTj6nMEfcXXPNNa6RZIYdXHldu3aNHPGtt97q0kOkGy9FEVeaPXu2UEdeGgMJBEAgPALGQBCX7/F0z/meRM9Azosq1a1b18VdpBN/zadLMoJMJZ25HTzCOhcSL83inJ3CtEOTJk0SkydPDmTqc55q/fXXX0/wzHXGj00Xx5IlSyZGjx6dC8i009G0l3OrnaKaKOTkZB5rol5kasj83uTB2+eeey4yfVQqMl4quZ4dPANXEMszqNSfScYYyCn94sd4AZMwOjIyFZE8bwygdLXTahdzv0WLFkrl5auQycG5zdf2+m2Xk5N57LdclesR86lQCl8GMV/4jKOowfRd5zaKunOtDicj8zjX2hGWvu+//37isMMOU4o5mF2FChUSDRs2TP6e46VFeIbA/fffX/l6nskn21l6wmIQRbm8DLJ57zm3vNQp/05GykzAyc48znxl4UmYbJzbqEgg7ouKdPp6EPel55MLZ50+bD3OBf2hYzgEwny/70VjY9C1NL4Jon+fZ6G23vOi/fbt23tROTDZV199VagbL9WFFAyB6N5QBqOv51LCdGReV1fkMM4844tXz3r7veDmm29W0u3aa6/1W1XW1/OPs3322celZ1wPnKwbggtBIIcIvPzyyy6f42dWvi97xSZyPpvN4yjMl66zytTD3Oo0aIqXIzT1SretU6dOFBgDq4OXX7zpppsSxuhvYfuMmTcSV111VXKpluXLlyvXy0vU8ItrY3YeaScw18lxAcsiZUdAdi9mV1r+XwVe/9r47LPPFvq7lY/xpY42N8ScOXMSPK2tVb8DDzwwYXydrIWOxqw+0mdo/fr1E+vXr/ekp2wKYWv7C30wv5WFdd8T6AIStjKy7oeNADFf2IS9lY+YzxsvHaWt/mvd11HXuHWy8rHux62XTvX/+eefieuvv94WX1lZBbHPL+35hUahpnRLzvLgJSQ1ArJ7Ue3qwpKKkxXiPr3uNcR9etnDqzYyX+Z8pMIlEOb7fS9UL730Umn82KVLFy9FCWW/+OILafnsAyVKlEisWLFCeG3YmTt37kwYM2a79DNmnwy76oIpH0tfGXd5tskYKUfdu3fPeHnHjh2Ty11kFAxQgPVi/TKlAQMGJKekzyQXxvnPP/+cjj76aFfRPXv2JJ7SDAkEQCB4AqeccgrNnz/fVnAhLHvFDZZNoWn8x7fxCOPAGCBFbdu2VSp61qxZyam2lYRDFNqxYweVLVuWeJspGQEpjRkzJpOYdueNIJj4f44xw1ta3Xia8gYNGpAxIweVK1eOjJflyaWqNm/eTL/99hsZnTO0cOFC4mkw06XzzjsvuSyl0XmbTgznMhCI05czqKblafD61yzGbDl0xRVXpLURP6dffPHFtDJRnOSlAo477jgyBrvYquOpZvk5EneaMGECXXbZZUI1eCpgXp6K/394SSrT/PIyW6effrqXYvNKFr7szZxx8ULM581OUUkj5ouKdPD1xOXLwbck/BLBSp0xL/v9/PPP0/jx44mXYvKbSpcuTS1btqSLLrqIWrduTby8cqEmXtKUlzYVJeNjUXrsscdEp5DnIAB/dgBJcxgnK8R9aQwT4ynEfTHC91G1zJe5yCj67n2ojktDJKDL0leNGjWixYsXC1tqfKyWcSlU4YWOzGOPPVa43HuRIkXooYceouuuu85xRXSHvXr1Er6zN2asJGOFgugUydea8n1IUpgj7oyOfNcoMuM+ceUZHdmRY+bltkS6OPMMB49cN7NCYzCRUMcFCxaYItiCAAgETKBQl71ijM7nn3kcMGJhccaa1dL6TT14W7Ro0cTWrVuFZUSdabw0VdKZ9Z44cWLU6gVa39dff53o0aNHwnixrNxmq93S7fP06BwHvPvuu4HqXMiFyXgXMpN0bQevf+n89ddfySUMZDw4n2esiXs6/tWrVyeMdaddz6Ju3bqlM3Nk57788ssEL1sg4sgzAPl51hmdEsJyua7ixYsntm/fHlk7daxIxJzzkMQE4uKFmE9sD11yEfPpYgl1PeLyZXUN9ZEEq+xs8fHHHyc4zjI+zhAuWSzjyl8Wd+rUKcEzyHCcifQvgTZt2kjjuTj7oHPNPrL7LtfaEYW+cbJC3BeFhbOvA3Ff9uziuFLmy5yPVLgEwny/74Vq5cqVpfEN36N33323l+KEsjzzI682Y65Cs99++yV49mnj42ChfJSZshl/OBZG8k8AM+oYXpRt4lkpeHaKTIm/pjCmPc0kFuh5Y1kNMtbNy1gmj/zmLz6iTsZ0WVSlShXasGGDrep69eoRz7SDBAIgEDyByZMnk9FpYiuYR6v//vvvZPzjt+Xn44FsZL7xrzT05hrr2ZPxAzFjPTwCmUci65AGDRqkPOPaunXrqGLFijqo7UsH4yUwGUtX0VtvvUXvvfceGVNKZlUez8DTqlWr5J+xfFhy9p2sCsJFQgJx+rJQIc0zwWuPgVSea4sWLSL+iiWOxLNy8YwxzmdPw4YN6YMPPiBjsEocaqXqNJbJTM70I/vyvHfv3nTvvfem5L3uGAMmadSoUcLL+DfXvHnzhOcKJRO+7M3ScfFCzOfNTnFJI+aLi7z3euPyZe+axn8FWPm3gTHghtauXUs//vgj8QyHvP3111+JZ8zh33jWvzJlyvivMA9LMAacE89YJErGgG46+eSTRaeQ5yAAf3YASXMYJyvEfWkMo9EpxH0aGSONKjJf5kui6LtPoxpOxUhAlxl1eHZ9nlVflng2xSeeeIKuuuoq6aoOsmud+cYHhLRx48bkrP7p/MJ5XdjHxhKmZAxwt1XD7xR5NvCSJUva8nHgjQAG6njjZZNetmwZ1a5d25YnOuAOd56qPcp08cUX06RJkzJWyYONTjrppIxyQQuwbqyjM/GDl5chQQIBEAieAA8YcL7kOuSQQ2j58uXBV6ZhibLAJuxg/5dffqEKFSooEenXrx/dddddSrJhC5166qnEHWmZUp06dWjp0qWZxHLyPHfS8oAdYwaJ5MBSHlzKfxws8/3Eg5OMEfXJv0qVKiW33DEpWtYxJwFoqnRcvqwpjoxqgdceRDyosEaNGrRr1649mY69K6+8kp555hlHbviHK1euTA7S4a018TP2nXfeUf4/Yr026H1eGowH+YsS67lkyRIyZu4TnVbK448bpkyZIpQdOHAgDRkyRHiuUDLhy94sHQcvxHzebKSTNGI+naxh1yUOX7ZrkDtHYJU7tspXTXlp6HTLn27atImMGWfztfmBtgv+rI4zLlaI+9RtpJsk4j7dLPKvPjJf5rNh993rSQRaMQFdBupwX7/KBBO8jP0dd9xBTZs2zbsPdx999FG6/vrrXTfmuHHj6IorrnDlI0OdAAbqqLNySW7ZsiX5VYXrhCODv4KVrV/nEA3s8Mwzz6TZs2dnLI+/iK1Vq1ZGuaAFzjnnHJoxY4atWGPJl+SXK+XLl7fl4wAEQCAYAvwlPs9mZU2F9OJLFvCHHex7WbP6zTffpObNm1tNFMs+f23CHWz8RWGm1KVLFxozZkwmMZwHgcAIxOXLgTUg4oLAyw7cmEaWXnjhBXum5Wjvvfemb775hg477DBLbri7/EUKz3DJX21bE8foPMCWBwLGnXiwEH98IEt+f5jz/+Jy5cpJv1Dijx7S1S/TK5/y4cverBkHL8R83mwEaRBQIRCHL6vopaMMWOlolcLSKV28WK1aNTKWeC0sID5aC39WhxcXK8R96jaCJAioEJD5Ml8bdt+9in6QiYeALgN10n1YJiLDA5P5HTj3Y5144onEH7elu8dFZeiWxwOy+YNlfm9kTTw5wNy5c61Z2PdIAAN1PAJzivPUTsbacc5s2zF/Xf/999/b8sI+aNSoUcbBQTwdFw82inpaKh61zF8z//333zYMF1xwAfHSPEggAALBE+DlfJzL3HFwwMtY7LvvvsFXqGGJsmAo7GC/a9eu9Mgjj2QkwoMV+QuzUqVKZZQNW4BfiPLIb5U0ceJEateunYooZEAgEAJx+XIgysdQCHjZofMMWccff7zrh6VV6sILL0wug2fNC2Ofp7MdPnw4DRgwgHbv3m2rgn8/8CAdXipWh9S4cWP66KOPhKrw7GL84oX/j2WbeDaeBg0aCC/ngcbcIWCs0y08XyiZ8GVvlo6DF2I+bzaCNAioEIjDl1X00lEGrHS0SmHpNHLkSOks6S1btqTXX3+9sID4aC38WR1eXKwQ96nbCJIgoEJA5st8bdh99yr6QSYeAroM1Lnlllvo/vvvzxoCD9zhd/a8fBT/8UoGvLRqrqXLL7+cnn/+eZva7Lu8+hD3YyJlRwADdbLjlrqKl416//33U8eiHf46lNc0jjLxV8CZlrOJa7mSYcOGUf/+/V04pk2bRueee64rHxkgAAL+CfDoXf66yZriGERorT/qfVnAH3awf9RRR9FXX32Vsbn8EnTBggUZ5aIQ4JmW7rzzTqWqeCkZfkmLBAJREYjLl6NqX9D1gJeb6EsvvUSXXHJJ2s6ee++9l3r37u2+OKCcn376iTp06CBcHrdmzZrJQTrVq1cPqDZ/xfBA+jZt2kgL4Q6L++67T3pe5cSoUaOoR48eQtFTTjnFtXSnUDDPM+HL3gwcBy/EfN5sBGkQUCEQhy+r6KWjDFjpaJX80Yn7TdavX08cw27dulXYMI6fp0+fLjzHH2fKYj2+oESJEsl+BZ55B4mkX92H3X+Vi+zjevYh7svFuwU660xA5susM559OlsuXN10GaizaNEi4mWtgkr8oRvPtMPvw6+++uq0S4cGVWcQ5cyZM4eaNWvmKmrw4ME0aNAgVz4y1AhgoI4aJ6nUrbfemrFjmp3OudyMtMCAThx44IHSqePNKnj023PPPWceRrLlf6q1a9d2zTDEU2bxl7i83AASCIBA8AT4K3TnMkb8z5P/iRZKkgX8YQb7Xtas7tu3L919991amINfis6fPz+jLnEN+MyoGATymkAcvpzLQMFLbD3+/zdkyBDxSSOXZ5588cUXXbPRSS9QPMG/CZ588kniAZEbN250XcXP3wkTJiSnk3WdjCGD/0ceeeSRtHTpUmntPBtO/fr1pedVTvDLm9dee00oWkjLdAoB/C8TvpyOjvtc1LwQ87ltgBwQCIJA1L4chM5xlQFWcZEvjHr79esXen8F38O8nFC6AeKFQRsDdbzYOY5nH+I+LxaCLAioEZD5Ml8dZt+9mnaQiouALgN1uP0nn3wyvffee4Gj4FV7brjhBurVq1dySfjAKwiwQPZFXqFnx44dtlLbt29P48ePt+XhwAMBA2xeJ+PrzoSBw/bXsGHDwNo8adIkW9nOusxjY3mswOrMVJDxMj5hvFzIqJcxJWmmogI/b0zhL9SrT58+gdeFAkEABP4l8Oqrr7r8zgh+E1E+l3Swhfk8dm7D1M3oZHKxd9ZvHs+YMSNMVZTL3rZtW6JYsWJKenfp0kW5XAiCQFAETJ9xboMqP9/KcXIyj/OtnV7bYyw7lbj44ovTPuv4f+Xtt9+eMJZr9Vq8S94YoJN49NFHE8ZXwsI6ua7bbrstYSyB5bo2zgxjuSuhvuZ9ZCxn61s9tsUBBxwgrcdYjtF3HflQgMncuc2HtoXRBicn8ziMurhMxHxhkUW5hU7A9F3nttC5iNrvZGQei2SRBwJeCTRp0kQaq5n3WhBbYxZ2r6rlpbyMZV421mej4mCFuM+n0XA5CAgIyHyZ85EKl0DY7/e9kOV320WKFAktHjIms0h8/PHHXlSKXNb4UE/Y/p49e0auSz5VmPdPubAdec2aNcIb0/mP5euvv47svjHWg1PS6d13341MJ7OiK6+8UqjbN998Y4pgCwIgEDABY9krl98Zy14FXIv+xTmfy+ZxmJoba1a72Jv1Wrcc5G3ZsiVMVZTLnj17tpLOrP/EiROVy4UgCARFwOo71v2gys+3cqyMrPv51s5s2mNM258w1obO+MwzlrpNZDtYZOXKlQkeHM8DWqz8rfvGMrkJXQZrOjnyYHqrrs7966+/3nmJ5+PPPvtMWkfx4sUT27dv91xmPl7gZG8e52Nbg2iTyce5DaJsURmI+URUkAcC/gk4fdg89l9y/pVgsnFu86+laFEcBPgFjPPeCvrY+EI7wYPEkYzP1R0fHZvHYOMmYLJxbt2SweUg7guOJUoCAZOA04etx6YMtoVHIOz3+16JjhkzRvo/2nrPZrtvrIqReP75572qFZl89+7dhe1fsGBBZDrkY0VY+srwGL+J1881BuykLeaNN96gc845J61MUCffeustOuuss9IWx9P5//7777TvvvumlQvypPESOrnesDFbg61Y46sMev/99215OAABEAiOAJa9+pelbApN4597cLAdJamuWX388ceT0SHluDqewwEDBtDQoUOVKl+3bl3yua4kDCEQCIhAHL4ckOqxFANe6bHzspC8FOSIESPImNklrbAxYIcuueSS5HrMhx9+uFCW49yvvvqKpk2bRlOnTiVeFipd4pidl8KqWrVqOrHYznE7v/vuO2n93E5eU9tPGjVqFPXo0UNYBC8FZny1JDxXaJnwZW8Wj5oXYj5v9oE0CKgSiNqXVfXSUQ6sdLRKfun022+/0aZNm4iXcnUmXjJWtqxsvXr1kkvKOq8xj/neNWZXpPLly5PsPjZlC2Ur4xBm/1Wuso2DFeK+XL1boLfOBGS+zDrj2aez5cLVTaelr8yW3n///dS3b1/atWuXmRXoln2B4ypjFvBAy/VbGMd/VapUoQ0bNtiK4jjv888/t+XhwBsBDNTxxksozQ5jLIElPGdmPvzww8l15szjMLePPfYYGcuRpK3iiCOOIGOWn7QyQZ/klxCdO3d2Fcv511xzjSsfGSAAAv4J8EvCVq1a2Qrif/Y8cK5UqVK2/Hw/kAX8YQX7v/76K1WoUEHpx0Tv3r3p3nvv1cIE/FJ0/vz5GXWpU6cOLV26NKMcBEAgaAJR+3LQ+kddHnipEf/ggw/ImPmRvv/+e6UL+PnOP1CN2XCSz/mffvqJ1q5dS5s3b1a63pjJh+6++24yZr1Tko9DiAcccSe0LPFA4I0bNybXp5bJqORfcMEF9NprrwlFBw4cKH3pI7wgjzPhy96MGyUvxHzebANpEPBCIEpf9qKXjrJgpaNVCkcnY8YdMmaRFDb46quvprFjxwrPIVNMAP4s5iLKjZoV4j6RFZAHAv4JyHyZSw6r796/1ighbAI6DtThNvMH1xzfhPWO3ZhlkBYvXkz8/kWXxGMgRIOH2EYcByL5IGA85PI6RTE1lnEjCqd7MsySyu/Vq1dknDNNUc96sUzU6YQTTkjxMNkYM/ok/vjjj6hVQX0gUDAEzjjjDJffFeKyV2xw87nj3IZ1M3hZs9qYdS0sNTyVa8wEkShWrJiUlZWdMSDUU9kQBoGgCFjvQ+t+UOXnWzlWRtb9fGtnEO35888/E7yUk5VT0Pt169ZNvPrqq0GoG3oZTzzxRFoWzZo1862DMYtRwviCWlpPtkuO+VZMwwJk96KGqmqhUpS8EPNpYXIokacEovTlXEcIVrluwdzWX7TkunlPjh49OrcbF4P2JjvnNgZVtK/Sycg8DktxxH1hkUW5hU7A9F3RttDZFHL7o3i/ny1f7s8yVrdJGLNMJ4wVbKT9WqJ7WiWvadOm2aoWynUtWrRwtbFo0aKJX375JZT6CqlQzKhjeITf9O2332Yc2damTZuMs+741cO8vm3btmQEjeahcPvll1/SkUceKTwXRibPumC8mHAV3bFjR3r66add+cgAARAIhkCJEiVox44dtsJ4OmL+Qr3QkmxkvvFPPxQUN954I/FsapnS3nvvTTyFdOnSpTOJhn7eeCFKRhCoVM/EiROpXbt2SrIQAoEgCUTty0HqHkdZ4OWd+g8//EDGmtA0fvz4tMs+qZbMz/eWLVvSRRddRK1btyZegjYX0uDBg9POZtO/f3/lpRJl7eWlwRo0aCA8Xbx48eQMRTxzDxJJl4IIK47JdeZRPvsQ8+X63QL9dSYQpS/rzEFFN7BSoQSZsAgceOCByX4NUfm8jCnP3IukTgD+rC8rxH3qtoEkCHghIHvucRn4zeuFZH7J6jqjjpMy9yPyO/nZs2cnZ9vh1SyCSG+++SY1b948iKJ8lcEziNeoUYP+/vtvWzk8Q/bkyZNteTjwTgADdbwzE17RqFGj5FRUwpNGJg+K4cExUaTDDjuMli9fLq2KO8M//fRT6fkwTvCyLiNGjHAVjR9rLiTIAIHACEybNo3OP/98W3kc9BbislcMQRbwhxXs8/qcKs99/v+xcOFCm53iOuABXHfeeadS9evWraOKFSsqyUIIBIIkELUvB6l7HGWBlz/q/HzmATv8w5N/mKr+zzjooIOS/4MvvPDC5ABIY7Yyf4rEcDUvWctL1MoSL1flXF5TJivLHzVqFPXo0UN4ml/o8G8FpH8JwJe93QlR8kLM5802kAYBLwSi9GUveukoC1Y6WqUwdPrxxx+pevXq0sby0rBlypSRnscJNwH4s5uJLCdqVoj7ZJZAPgj4IyDzZS5VtR/Gnwa4WkcCuTJQx8rOmGmHeCn5Dz/8MPX3zTffEOd7TZdddlnyQ0Kv1wUtP2zYMOKP9ZyJ3z8aMwo5s3HskQAG6ngEJhO///776ZZbbpGdTub//PPPxJ32YSauI9OL06jXjNu9ezdVrVqVWDdrqlWrViBfKVvLxD4IgMAeAsaSFDRnzpw9GcYeD+RbtmyZLa9QDmQBfxjBvpc1q42lEYUDGeOwC78UnT9/fsaqeX1UnikNCQTiIBClL8fRvqDrBK/giP7111/JwTr8MmLNmjXEW37e84w5HOta//LhZYQxrS3NnDlTCpAHLlWuXFl6XuUEf33DA35EiQeP8iyASP8SgC97uxOi4oWYz5tdIA0CXglE5cte9dJRHqx0tEph6PT666/TeeedJ2xszZo1acWKFcJzyJQTgD/L2TjPRMkKcZ+TPo5BIDgCMl/mGsLouw9Oc5QUJoFcHKgj4rFhw4bkgJunnnqKPv/8c5GIMK9kyZK0ceNGinOmafa/2rVr0/fff2/TkfsDV69eTbxaBJI/Ahio449f6ur169cnp37auXNnKs+5M2HCBLrkkkuc2YEev/rqq8Rf7soSOw2/VKhUqZJMJPD8KVOmJKf5dxZ81113Ub9+/ZzZOAYBEAiIAJa9soOUBfxhBPuvvPJKcokTuwbiI11GHm/fvp3Kli1L/CI6U+rSpQuNGTMmkxjOg0AoBKL05VAaEHGh4BUx8Dyq7uijj5Z2IFSpUiU5WMlPc/n/b7ly5aTLJPByjKeffrqfKvLqWviyN3NGxQsxnze7QBoEvBKIype96qWjPFjpaJXC0Gno0KE0YMAAYWN52Vfuq0byRgD+rM4rSlaI+9TtAkkQ8EpA5stcThh99171g3w8BPJloI6V3qJFi4gn/uDxAiqJZ+M5/PDDVURDkXn33Xfp1FNPdZXdp08fuueee1z5yPBOAAN1vDOTXtGpUycaO3Zs2vNPPPGE9HwQJ3r27EkjR46UFsXr2fG6dlEmnhJ/6tSptip5wNCqVauIO/mRQAAEgifwxhtvuKad44B369atxAN4CjHJAv4wgv2bbrqJHnrooYyY+VnIo6J1mHlh7ty5dMYZZ2TUmQUmTpxI7dq1U5KFEAgETSBKXw5a9zjKA684qOdHnemW9uXZdqZPn+6roUuWLCFekleUihcvTrxMQpxfDYn0ijMPvuyNflS8EPN5swukQcArgah82ateOsqDlY5WKQydLr74Ypo0aZKwsYMGDaLBgwcLzyFTTgD+LGfjPBMlK8R9Tvo4BoHgCMh8mWsIo+8+OM1RUpgE8nGgjsmLY6cOHTrQjh07zCzhlt/n83v9uFLHjh1p3LhxrurjHkDkUiiHMzBQJ0Djfffdd3TEEUdI15qrUKFCciqoYsWKBVjrnqJ4ialq1aoRz+4jSzx9/VlnnSU7HXg+68I6sW7WFETnvrU87IMACNgJ8D/vWbNm2TILfbk5WcAfRrCvumZ1w4YNafHixTY7xXXAHWh33HGHUvXr1q3LuMyiUkEQAoEsCETpy1mop90l4KWdSXJGoYsuuoj4q1FRuvHGG+nBBx8UnVLOGzVqFPXo0UMoz0sxzps3T3iuUDPhy94sHxUvxHze7AJpEPBKICpf9qqXjvJgpaNVCkMn7mtyLodgtpxn0+FZdZC8EYA/q/OKkhXiPnW7QBIEvBKQ+TKXE0bfvVf9IB8PgbgG6vCynfy+n5d34tlswnqnz4N12rZtm/Yef+aZZ+jKK6+MxQBbtmxJvgPatm2brf4mTZrQ+++/b8vDQfYEMFAne3bCK9mpXn75ZeE5zgzTqSZPnkxt2rSR1h3HbDojRoyg3r17u3R66aWXiL+4QAIBEAiHAK9fyUsZWRMPwpBNR2yVy9d9WcAfdLDPa44edNBBaQMskzHPgsYBpw7ptNNOU3opWqdOHVq6dKkOKkOHAiUQlS/nC17wyhdLRt+OW2+9le677z5hxTy9LU9z6yc1a9aM5syZIyxi4MCBNGTIEOG5Qs2EL3uzfBS8EPN5swmkQSAbAlH4cjZ66XgNWOlolfzX6c8//6TSpUtL+z/4RVfNmjXzH0TALYQ/qwONihXiPnWbQBIEsiEg82UuK+i++2z0wzXxEIhyoM6uXbuIl/PkVRJ+++23VIN5dQrOu/rqq1N5Qe6k+0iO6+HBPOne+wepi7OsJ598kjp37uzMJs6/5pprXPnIyI4ABupkx016Ff8AOfLII10vyM0LjjnmGPrkk0/Mw0C3ohk0zAr22msv+vTTT6l+/fpmViTbunXrul7olitXjtauXRvaKMRIGoZKQEBjAjNmzKBzzjnHpiEHu4W87BXDkAX8QQf7XtasnjJlCp1//vk2W8VxwFMs7r///vTXX39lrL5Lly40ZsyYjHIQAIGwCETly2HpH3W54BU18fypj5/1N9xwg7BB9957r3AwvlBYkMlfXdeuXVva4fb222/T6aefLriycLPgy95sHwUvxHzebAJpEMiGQBS+nI1eOl4DVjpaJf91+uCDD+jEE08UNpSX+OalTJG8E4A/qzOLihXiPnWbQBIEsiEg82UuK+i++2z0wzXxEIhqoM6aNWvovPPOo88++0za0OHDhxN/0BZ0evfdd+nUU0+VFssz1/AMNnEkrnfBggW2qvfdd1/66aefaL/99rPl4yB7Ahiokz076ZXccd23b1/p+TCm/eR16s4++2xpnTy6jUe5RZnYgUUPkG7duhFPdY8EAiAQDgFe3u6tt96yFV7oy14xDFnAH3Swr7pmNQ+g3LhxY3KAjM1YMRzw8iI8o45KmjhxIrVr105FFDIgEAqBqHw5FOVjKBS8YoCeJ1Xykrm8XK0o8f+60aNHi04p5fHvFv79IkrFixdPvtTZZ599RKcLNg++7M30UfBCzOfNJpAGgWwIROHL2eil4zVgpaNV8l+ndAO7sZRp9vaHP6uzi4oV4j51m0ASBLIhIPNlLivovvts9MM18RCIaqBOy5Ytafr06WkbefTRR6cdyJP24jQneVWMUqVKSe/zn3/+Obl6Q5oiQjnFKyrwRBzO1LFjR3r66aed2Tj2QQADdXzAk13KU2Qde+yx9MUXXwhFKlasSF999RUdcMABwvNeM9mRjzrqKPrhhx+El/LXqgsXLkxORSoUCCmTp8QSDQ7iUYn8UEMCARAIh4Bo2Suetq9///7hVJgjpcoC/qCDfZ65TPb8t6Jq0KBBcqYza15c+7ws2qBBg5SqX7duXXJtUiVhCIFACASi8uUQVI+lSPCKBXteVMpLGVSrVk34JTR3Yrz++utZtfPOO+8kXtpKlvBSR0wGvizmIsuNghdiPhl95INAcASi8OXgtI23JLCKl3+h1n7dddfR448/Lmy+34HdwkILJBP+rG7oqFgh7lO3CSRBIBsCMl/msoLuu89GP1wTD4EoBurwR8mXXnqpUgPXr19PFSpUUJL1IsRjBTZt2uS6hN/7q7xncl0YQEbv3r1pxIgRrpL4g2/ut0MKjgAG6gTH0lYST+feuHHj5GwJthP/O2jbti29+OKLolOe866//np69NFHhdfxSLyPPvoouRyXUCCkTF5ip1KlSrRlyxZbDTyAadGiRbY8HIAACARHQDS7Fge6hb7sFROWBfxBBvte1qzu0aMHjRw5Mjjj+yjpjDPOoLlz52YsoU6dOq7lDDNeBAEQCJhAFL4csMqxFgdeseLP+cp5llCeLdSZatasmfxIQHZ/OeXN42HDhmUcOMyDeIYMGWJegu3/CMhYBxnH5BPssHkh5sunuwVt0ZlA2L6sc9u96gZWXolBPggC3PfN/c6iNHbsWLr66qtFp5CXgQD8OQMgy+koWCHuswDHLgiEREDmy1wdfvOGBD0Hio1ioA4vu/7OO+8o0Vi+fDkdcsghSrKqQv/88w/xh/d//fWX65K43h/t3r2bqlatSjybjzVh1Q4rjeD2MVAnOJauknhtuTPPPJN27tzpOscZQXxZwJ3YgwcPFpbP/9wmTJgQyxIl48aNI54Cy5keeugh6tq1qzMbxyAAAgEREC0lwbNqffvttwHVkLvFyAL+IIP9yZMnU5s2bZQghbEMolLFDiH+H7X//vsTz86WKXXp0oV4amskEIiTQBS+HGf7gq4bvIImWljl8brTPCiHZwx1pkmTJin/z+Nr77rrLrr99tudxbiO3377beKOEiQ7AfiynUemo7B5IebLZAGcB4FgCITty8FoqUcpYKWHHQpJC36xtN9++9G2bduEzeYPNfmDTSTvBODP6syiYIW4T90ekASBbAnIfJnLC7LvPlv9cF08BKIYqFO+fHniAZmZUunSpZMzTqe7VzOVITr/ySefSOOl+fPn00knnSS6LNS8KVOmUOvWrV11cL9ev379XPnI8EcAA3X88ct49SuvvELt27cXjobji2+44YbkjArFihXLWJZV4O+//05OGc9fpYrS3nvvTfzlwpVXXik6HXreqaeeSjxQyZr22Wcf4s7+smXLWrOxDwIgECABLHslhykLooIM9rt160YPPvigXIn/nWFdOAAMagnEjBWmEeCAT3W6Qp4Ksl27dmlKwykQCJ9AFL4cfiuiqwG8omOdrzV16tQp+bvC2T5eyvbTTz+Vzlhnyv/222904403Jj8gMPNk2+LFiyc7Pvh3A5KdAHzZziPTUdi8EPNlsgDOg0AwBML25WC01KNXq6R9AABAAElEQVQUsNLDDoWkBX8QxrPuilKRIkWIl1Hl2A7JOwH4szqzKFgh7lO3ByRBIFsCMl/m8oLsu89WP1wXD4GwB+rwUla8MoxKOuuss2jmzJkqop5kZDNPH3fccfTxxx97Kiso4VatWtHUqVNtxfGYg1WrVlGVKlVs+TjwTwADdfwzzFgCvwTlG1u0xhxfzJ3czz77LPFapyrpu+++S04d+v777wvFuWObl9U6//zzhefDzuRlv3gKLGfil7v8khcJBEAgHAKzZs2i5s2b2wrnIBfLXv2LRBbwBxnsq65ZzXJLliyx2Squg6FDh9KAAQOUql+3bh1VrFhRSRZCIBAWgSh8OSzd4ygXvOKgnl918lfSPEvoBx984GoYr+PNHweUKFHCdY6n7eXfOPy1jcrXSVwADxzl9a6R3ATgy24m6XLC5oWYLx19nAOB4AiE7cvBaRp/SWAVvw0KTQPue77kkkuEzT7yyCPpyy+/FJ5DZmYC8OfMjEyJKFgh7jNpYwsC4RGQ+TLXGGTffXgtQMlhEAh7oM57771HJ598ckbVeQAyzxTI7/KDTLzE1KGHHkqrV692FRvXB9M8eKlatWrEullTixYtaPr06dYs7AdEAAN1AgKZqRgeXHPFFVdI1+3da6+96Nxzz03OsHP88ce7Zp3hpUl4YA4vOcKz9PD0oqJUt25deuaZZ4hH28WV+vfvT6KZft58803XIIK4dES9IJCPBM455xyaMWOGrWlY9moPDlnAH1Swz2t28ghslfL4a5xRo0btUS7GvWbNmtGcOXMyasBfyi1dujSjHARAIGwCYfty2PpHXT54RU08P+vjDw54EI3ohUvDhg2pe/fu9N///jc5YOebb75JDrZ58skn6ZdffrEBadSoUXIAsez/ycCBA4mX9kVyE4Avu5mkywmTF2K+dORxDgSCJRCmLwerafylgVX8Nig0DXgw9t133y1sNs8uP378eOE5ZGYmAH/OzMiUCJsV4j6TNLYgEC4BmS9zrSp97eFqh9LjIhD2QB3+kLpBgwYZmxfWkk/PP/88XX755a76+T0/68YDhKJOI0aMoN69e7uqfemll+jiiy925SPDPwEM1PHPULkEHlzzwAMP0KBBg5LTf6a7kF/28qg1XhaFpwrldepka/5yOeywffr0Sc6KEOe0orwkV40aNWjt2rW25lWvXp1WrFhBPCAJCQRAIBwCPO0cLy9nTTzDDg+SQyLp0hxBBfv5/uP98MMPJ375igQCcROQ/XgPypfjbl/Q9YNX0EQLszweqMNfGX311VcuAMceeyzxAFQM1HGhCTQDvuwNZ5i8EPN5swWkQcAPgTB92Y9eOl4LVjpaJb91wkCd8OwLf1ZnGzYrxH3qtoAkCPghIPNlLhP9fX7I5va1YQ/U+eOPP6hMmTJSSOXKlUvOIh3G6jW//vor1atXj/j/jDXxu/4PP/yQuK8tjsSDhJwf1zEHfudfrFixOFTK+zoxUCcGE2/ZsoV4pNxjjz1Gn332mS8N9t13X7rmmmvo5ptvTg6Q8VVYABfzbB48q4cz8bIqd9xxhzMbxyAAAgER4IFwhxxyiKu0119/nVq2bOnKL8QMWcAfVLDPMwd07txZCS3PjHbhhRcqyYYpxLO17b///rR9+/aM1Vx33XX06KOPZpSDAAiETSBsXw5b/6jLB6+oiedvfTwYmL+Ofueddzw3kpfm5Y8Kbr311uTsc/x7SJTefvttOv3000WnCj4PvuztFgiTF2I+b7aANAj4IRCmL/vRS8drwUpHq+S3TqJZnc0WDx8+PBn3mcfYeiMAf1bnFTYrxH3qtoAkCPghIPNlLjOovns/+uHaeAiEPVCHW1WzZk1atWpVqoHHHHMMtW3bNrlqDa9+s99++6XOBbXD9/QFF1xAU6ZMcRU5ePDg5GQfrhMRZCxYsICaNGniqkmn1SFcyuVBBgbqxGzEjz/+ODlg56233qI1a9YoaVO6dGk688wzk0tltW7dOvmSVenCCIR46qtJkybZauJ/st9//71wEIFNEAcgAAJZE+Dp6HhaOmvi2bX4RVjRokWt2QW7Lwv4gwr2eWT1tGnTlPjySOmDDjpISTZMobFjx1KnTp2UqnjuueeEUzEqXQwhEAiQQNi+HKCqWhQFXlqYIa+UeO2115LT4C5btixju/hrGx6YysviHnzwwbRw4ULijg5R4rhl8+bNxIN6kNwE4MtuJulywuSFmC8deZwDgWAJhOnLwWoaf2lgFb8NCk0D0azOJgPu5+a+a6TsCMCf1bmFzQpxn7otIAkCfgjIfJnLDKrv3o9+uDYeAlEM1Bk6dGhypRqzhbxkO89os/fee5tZgW55VZprr72WnnrqKVe5J510Es2dOzeWJa9YGf4InQeoOhNPOHL00Uc7s3EcEAEM1AkIZBDF8At1XlaEp5XigS1bt25NvmDnHz5Vq1ZN/VWoUEHLJaQ2bNhArCvP0GBNp512WvLhYs3DPgiAQLAE+BnhXHLurLPOopkzZwZbUQ6XJgv4gwj2OYBi3rt27cpIiJc03LhxY0a5sAX++usvqlWrFv34449KVS1atCi2KReVFIRQwRAI05fzESJ45aNV428T/7+bM2cOff7556k//h3Dg2x4QA7P8tesWTO69NJLk0v5mhqLOlnMc6eccgrNmzfPPMTWQQC+7ACS4TAsXoj5MoDHaRAImEBYvhywmloUB1ZamKFglODlGtJ9fPTLL79Q+fLlC4ZH0A2FP6sTDZMV4j51O0ASBPwSkPkylxtE371f/XB9PAREfUgNGzakxYsXB6bQ+vXrqXbt2skP3s1C27VrR88++2zgSz3t2LEj+SE0r7bgTNwn9sYbbxCvohNH4vEIlSpVsnFgPXgJLn4vhBQeAQzUCY9twZX8wAMPJJfgcjacH2gdOnRwZuMYBEAgIAIrV65MvhRzFsf/2EVL0TnlCuVYFvD7DfY5MOQvxTZt2qSM8quvviJe7zOuxINBu3btSvyVm2riZ3z37t1VxSEHAqERCMuXQ1M45oLBK2YDoHobgXRfpA4cOJCGDBlik8fBHgLw5T0sVPbC4IWYT4U8ZEAgWAJh+HKwGupTGljpY4tC0GT27NnSGXP4JQ8vmYqUPQH4szq7sFgh7lO3ASRBIAgCMl/msv323QehH8qIh0AUA3W4ZS+88EJyqXdrK3lZdl6NgD9GCyJNnjyZevXqRStWrHAV17x5c3r11VepZMmSrnNRZYwbN446duzoqu6hhx5KvkdynUBGYAQwUCcwlCiofv369MUXX9hAlClTJvnjLM4HjE0hHIBAHhJwTs/HTeTlI/7888/YpsnTEbMs4JcF+3/88UcycOJZwnbv3p3841loeEAOz4jz7bffJqdB5KkQvSaeceCiiy6iE044ITlS+cADD0zaiqdULFKkCJUoUYJ49jTO95JYP9aLt9yuf/75JznLz/bt25MzLn333XfJ89OnT0/KeCmb+fEMaeeeey5Vrlw5qR8vacI68x/rzEszVq9e3UuxkAUBzwS8+rLnCvLsAvDKM4PmcHP4f1K5cuWkA1vffvtt4o4QJDEB+LKYiyzXCy/EfHaKzA4xn50JjuIj4MWX49NSj5rBSg87FIoW9913H916663C5rZo0YK4zwEpewLwZ3V2Xlkh7rOzZX6I++xMcBQPAZkvszayvvt4NEWtURKIaqAOt4kH0XB91sTv2G688Ua64YYbkjNHW8+p7PM7GR7cPHLkSOmqMzzJxRNPPJF8n6dSZlgyp556Kr377ru24vkdFg++Llu2rC0fB8ESwECdYHkWbGk89dVxxx3naj+vtffYY4+58pEBAiAQHIErrriCnnvuOVuBPJMOz6iDtIeALOAXBfs8grlt27bJwTl7Soh2jwe/sF152RCVxDMr8VSEv/32m4p4aDKdOnVKBpehVYCCC56AF18ueFgGAPDCXaALAV7T+phjjhGqw50fmzdvTi6dJRRAJnzZ4z2g+uxDzOcRrEUcMZ8FBnZDI6Dqy6EpkEMFg1UOGSsPVOWXSuPHjxe2pG/fvnT33XcLzyFTjQD8WY0TS3lhhbhPnatTEnGfkwiOgyYg82WuR9R3H3T9KE9PAlEO1GECo0ePpp49e9Lff//tAvLf//6XeHmqevXqJf+OOOII2+Ca33//nX7++efkH39IPW3atOQgnW3btrnK4gxebYFnq9HhgzVefaFWrVouPXkJsIkTJ7rykREsAQzUCZZnwZbGIwrHjBnjav+CBQuocePGrnxkgAAIBEeAX3rxyy9rmjlzJp111lnWrILflwX8omD/4osvpkmTJsXOjJen4oBNJT3++ON03XXXqYiGKsNBHc/cgwQCYRHw4sth6ZBL5YJXLlkrv3UdPnw49enTR9hI7uyYN2+e8Bwy/yUAX/Z2J6jyQsznjatVGjGflQb2wyKg6sth1Z9L5YJVLlkr93Xll1RffvmlsCH8Qodf7CBlTwD+rM7OCyvEfepcnZKI+5xEcBw0AZkvcz2ivvug60d5ehKIeqAOU+DVE3iwDr/bTpf22msv4hVleNYZXoFhx44d6cRT5/bdd18aNGgQde/enYoWLZrKj3Onf//+NGzYMJcKb775JvGyXEjhEsBAnXD5FkTp/ADi9Yf5K1hrOvLII6U/2qxy2AcBEMiewPLly+mwww6zFcDLSqxbtw7LXtmoePvKhqd91eGFIQejHBiqJA6mOKiKO/EAMR4ohgQCYRGQ/XjHD3cxcfASc0Fu9ASaNWtGc+bMEVY8cOBAGjJkiPAcMv8lAF/2dieo8kLM542rVRoxn5UG9sMioOrLYdWfS+WCVS5ZK7d15aW2+SUTLxEuSkuXLqU6deqITiFPkQD8WRGUIeaFFeI+da5OScR9TiI4DpqAzJe5HvT3BU07d8qLY6COSWfy5Mn06KOPEi/TLpphx5RT2ZYqVYrOPvtsatOmDbVs2ZJKly6tclkkMty2GjVq0Nq1a231Va9enVasWEE8IAkpXAIYqBMu34Io/YUXXqD27du72jpixIjkun6uE8gAARAIjMA999xDt912m628a665hp588klbHg68/XjndUF5gMyff/6ZDEZ4dDP/8dIcPEqat6L9YsWKEf/xslX8I4I7rkR/u3btSo6y5oGO/McdXdZ9/nHCywlOnTqVypcvr2S+JUuW0Lnnnktr1qxJdlQUKVIkqQvrk05nbgfLsDwnkb5mnlVHc9/c/vPPP1StWrXkcl08MwISCIRFQPbjHT/cxcTBS8wFudES+OWXX6hKlSrSFzpz584l7jhHkhOAL8vZiM6o8kLMJ45VzfjOGqOaeYj5RHcc8sIioOrLYdWfS+WCVS5ZK7d1/eSTT5LLbotaUbJkSdqyZQte6ojgeMiDP6vD8sIKcR/iPvU7C5JRE5D5MuuB/r6oraFPfXEO1DEp8HJWvHQiz7Tz6aef0tdffy3t2+JreBBOxYoVk5NbHHrooXTeeeclV74oUaKEWaRW2xkzZtA555zj0mnAgAF0xx13uPKRETwBDNQJnmnBlSj6OpZfaP/4449UoUKFguOBBoNAlASOPfZY4k4Sa8KUdFYae/ZlAT+C/T2MsAcCuUAAvuzNSuDljRekiZYtW0Y8cIa/+Nm6dSs1bdqUuHPBTxJ1rpjl8e8F/nKHB7kiyQnAl+VsRGfAS0QFeSCQewTgy+o2Ayt1VpD0R+Dpp5+mq6++WljICSecQB988IHwHDLVCcCfwUqdACRBID8IyJ573Dr03eeHjbNphagvqWHDhrR48eJsigvkmp07d9Kvv/5Kv//+e3KVGf7Qm/vPeNUZHqDDg5ZzKYmWhWR//P777+mQQw7JpabkrK4YqJOzptND8ZUrVyad1fnPslWrVvTaa6/poSS0AIE8JfDDDz+4Xpxh2Su5sWUBv/P5JS8BZ0AABHQgAF/2ZgXw8sarkKV5lox+/foRd4TwTGpm4q9+XnzxxeRXQGael+22bduobt26tGrVKuFlN998M91///3Cc8jcQwC+vIeFyh54qVCCDAjoTwC+rG4jsFJnBUl/BLp3706jR48WFtKtWzcaNWqU8Bwy1QnAn8FKnQAkQSA/CMiee9w69N3nh42zaYWOA3WyaYeu12zYsCE5+zUPPrImnvGaP+BDioYABupEwzlvaxk8eDANGTLE1b4pU6bQ+eef78pHBgiAQHAE7r33Xurbt6+twE6dOhFP5YrkJiAL+BHsu1khBwR0JgBf9mYd8PLGq5Clhw0bRv379xciOPjgg4kHCGeT+vTpQ8OHDxdeylMC8ww+Bx10kPA8MvcQgC/vYaGyB14qlCADAvoTgC+r2wis1FlB0h8Bfnkzb948YSHjx4+n9u3bC88hU50A/Bms1AlAEgTyg4DsucetQ999ftg4m1ZgoE421NSveeCBB4g/nnOmZ599ljp06ODMxnFIBDBQJySwhVAsf3XLU185v47l6b142asiRYoUAga0EQRiI9CoUSPXNH9vvfUWnXnmmbHppHPFsoAfwb7OVoNuIOAmAF92M0mXA17p6OCcSWD9+vVUrVo120w65jlzu3r16qSMeayynTlzZnImHusMPdbreCYdUaeAVQb7/xKAL3u7E8DLGy9Ig4CuBODL6pYBK3VWkPRHoGzZssmlHkSlLF++HMskiMB4zIM/qwMDK3VWkAQBnQnIfJl1Rt+9zpYLVzcM1AmXb/369emLL76wVVKmTBn66aefcm4JL1sjcuwAA3VyzGA6qTt79mzhgIBevXrRiBEjdFIVuoBA3hFYsWKFq/OjfPnyyX+iGCQnNrcs4EewL+aFXBDQlQB82ZtlwMsbr0KVnjZtWsbZMH/55RfiWEM1zZo1K1nmjh07hJe0bduWJk6cSLJ7VHhRAWfKOCGOEd8U4CXmglwQyDUC8GV1i4GVOitIZk+AP9asWbOmsIBKlSol+6SEJ5HpiQD8WR0XWKmzgiQI6ExA5susM37z6my5cHXDQJ3w+C5atIiOO+44VwXXXnstPfbYY658ZIRHAAN1wmOb9yVfdtllNGHCBFc7v/76azriiCNc+cgAARAIjgAvIcFLSVhT586d6fHHH7dmYd9CQBbwI9i3QMIuCOQAAfiyNyOBlzdehSp911130e233y5tfr169ejzzz+XnneeGDduHF1//fW0fft256nkcZMmTYgH/ZcoUUJ4HpluAvBlN5N0OeCVjg7OgUDuEIAvq9sKrNRZQTJ7AlOmTKHWrVsLC2jXrl1yELbwJDI9EYA/q+MCK3VWkAQBnQnIfJl1Rt+9zpYLVzcM1AmP7w033EBjxoxxVbBgwQJq3LixKx8Z4RHAQJ3w2OZ1yZs2baLKlSuT8wtZdmB2ZCQQAIFwCfBoVx71ak1Y9spKw70vC/gR7LtZIQcEdCYAX/ZmHfDyxqtQpR955BHq2rWrtPkjR46kHj16SM+bJ37++Wfir2+mTp1qZrm2F198MfFAHgzScaFJmwFfTovHdRK8XEiQAQI5SQC+rG42sFJnBcnsCQwaNIjuuOMOYQGPPvooXXfddcJzyPRGAP6szgus1FlBEgR0JiDzZdYZffc6Wy5c3TBQJxy+/F6fZ0LcvHmzrYIjjzySvvzyS1seDsIngIE64TPOyxpknfk8mwfP6oEEAiAQHoGVK1fSwQcfbKsAy17ZcAgPZAE/gn0hLmSCgLYE4MveTANe3ngVqvSyZcuodu3awubz19E8i6bsXuKLPvzwQ3r66aeTX1H/8ccfwnL22WcfGjhwIPXt2zdtWcKLkSllhjhGfHPI7lfwEvNCLgjoSgC+rG4ZsFJnBcnsCZx77rn0xhtvCAtYvXo1VatWTXgOmd4IwJ/VeYGVOitIgoDOBGS+zDrjN5zOlgtXNwzUCYfvCy+8QO3bt3cVPmLECOrVq5crHxnhEsBAnXD55m3pjRo1osWLF9vaV7JkSVq3bh2VLl3alo8DEACBYAnwgDjnV0pY9iozY1nAj2A/MztIgIBOBODL3qwBXt54FbL0OeecQzNmzHAh2Hvvval69epUo0YNKlWqFPGAmyJFitCuXbvoxx9/pG+//ZZkg3PMwi644AK6//77qWbNmmYWth4JwJe9AQMvb7wgDQK6EoAvq1sGrNRZQTJ7Ajy7Ovf9OlP9+vVpyZIlzmwcZ0kA/qwODqzUWUESBHQmIPNl1hl99zpbLlzdMFAnHL7NmjWjOXPm2AovWrRoso+vQoUKtnwchE8AA3XCZ5x3NfAPrwYNGrja1aFDB3r22Wdd+cgAARAIlsC0adPo/PPPtxU6b948OuWUU2x5OLATkAX8CPbtnHAEAroTgC97sxB4eeNVyNI88KZTp06BxfNly5ZNfqFzzTXXCH87FDLrbNoOX/ZGDby88YI0COhKAL6sbhmwUmcFyewI8AAdHqgjSv369aO77rpLdAp5WRCAP6tDAyt1VpAEAZ0JyHyZdUbfvc6WC1c3DNQJni+v1nHIIYe4/KpVq1b02muvBV8hSsxIAAN1MiKCgJNA9+7dafTo0c5smjt3Lp122mmufGSAAAgES2D37t10xRVX0EsvvUR77bUX3Xjjjcmv1IOtJf9KkwX8CPbzz9ZoUX4TgC97sy94eeMFaaKvv/6annrqKXrnnXfoq6++Il67WiXtu+++dNxxx1Hjxo2Tf82bN0/OvqNyLWQyE4AvZ2ZklQAvKw3sg0DuEoAvq9sOrNRZQTI7ArzkFS99JUrvv/8+NWnSRHQKeVkQgD+rQwMrdVaQBAGdCch8mXVG373OlgtXNwzUCZ7v4MGDaciQIa6Cp0yZ4pocwCWEjFAIYKBOKFjzt9CdO3cmv57YuHGjrZGHHnooLVu2jNL9Q7VdgAMQAAHfBH7//fdkGWXKlPFdViEUIHs+IdgvBOujjflEAL7szZrg5Y0XpO0EeHDw2rVr6c8//0z9bd26NTl4h5e9PeCAA4hnzuG/gw46KDmA2F4CjoIiAF/2RhK8vPGCNAjoSgC+rG4ZsFJnBcnsCPBLHX6540zlypWjn3/+GXGgE4yPY/izOjywUmcFSRDQmYDMl1ln9N3rbLlwdcNAnWD5/vPPP8nZdFatWmUruGLFisllr3iZe6ToCWCgTvTMc7rGl19+mdq2betqw5133km33367Kx8ZIAACIKALAVnAj2BfFwtBDxBQIwBfVuNkSoGXSQJbEMhtAvBlb/YDL2+8IA0CuhKAL6tbBqzUWUFyD4E//viDFi5cSPzCpl69enTMMceQ7CXNmWeeSbNnz95z8f/2brjhBnr44Ydd+cjIngD8WZ0dWKmzgiQI6ExA5susM/rudbZcuLphoE6wfDmO43jOmXr16kUjRoxwZuM4IgIYqBMR6HyppkWLFjRz5kxbc3jpHV7Xrlq1arZ8HIAACICATgRkAT+CfZ2sBF1AIDMB+HJmRlYJ8LLSwD4I5C4B+LI324GXN16QBgFdCcCX1S0DVuqsIPnvS88xY8ZQ7969iWdLNFPVqlVp1qxZVKdOHTMrud21axftv//+tG3bNls+H/BAn0aNGrnykZE9AfizOjuwUmcFSRDQmYDMl1ln9N3rbLlwdcNAnWD5XnbZZTRhwgRXoV9//TUdccQRrnxkREMAA3Wi4ZwXtaxZs4Zq1KhBPD2WNTVv3pzefPNNaxb2QQAEQEA7ArKAH8G+dqaCQiCQlgB8OS0e10nwciFBBgjkJAH4sjezgZc3XpAGAV0JwJfVLQNW6qwgSSR68WVyadiwIS1evNg8TG7nz59Pp5xyii2PD44++mj67LPPXPnI8EcA/qzOD6zUWUESBHQmIPNl1hl99zpbLlzdRPGKKE4JV4v8KH3Tpk1UuXLl5FL21hY1btyYFixYYM3CfsQEMFAnYuC5XN3QoUNpwIABriZMnDiR2rVr58pHBgiAAAjoREAW8CPY18lK0AUEMhOAL2dmZJUALysN7INA7hKAL3uzHXh54wVpENCVAHxZ3TJgpc6q0CV5mSueMWfHjh1CFHwvbdiwgQ444IDU+Z49e9LIkSNTx+bO888/T/x1NlKwBODP6jzBSp0VJEFAZwIyX2ad0Xevs+XC1Q0DdYLj+8gjj1DXrl1dBT7++OPUuXNnVz4yoiOQ9wN1HnjgAbr55pttRI8//nj66KOPbHk4yEyAv5L4/PPPbYL8o+2nn36i4sWL2/JxAAIgAAK6EZAF/Aj2dbMU9AGB9ATgy+n5OM+Cl5MIjkEgNwnAl73ZDby88YI0COhKAL6sbhmwUmdV6JLjxo2jjh07psXAg3mqV6+elOE+k4MPPpg4z5oOPfRQ+vbbb2nvvfe2ZmM/AALwZ3WIYKXOCpIgoDMBmS+zzui719ly4eqGgTrB8eVlSp0zJpYsWZLWrVtHpUuXDq4ilOSZQN4P1Bk7dix16tTJBqZp06Y0e/ZsWx4OMhPgdYrXrl1rE7zpppto9OjRtjwcgAAIgICOBGQBP4J9Ha0FnUBATgC+LGcjOgNeIirIA4HcIwBf9mYz8PLGC9IgoCsB+LK6ZcBKnVWhS/bo0YNGjRolxcAfZfKMOuY9NWXKFGrdurVLfurUqXTeeee58pHhn4DJ3lkS+q+cRCh1nzrPgJWTCI5BQG8Csuceaw1/1tt2YWqHgTrB0F2yZAk1aNDAVViHDh3o2WefdeUjI1oCeT9Qh0eI8Ugxa+LpOtnBkbwRaNmyJU2fPj11Ec+is2zZMqpWrVoqDzsgAAIgoCsBWcCPYF9Xi0EvEBATgC+LuchywUtGBvkgkFsE4Mve7AVe3nhBGgR0JQBfVrcMWKmzKnRJ/ujyoYcekmLo378/DR06NHme+0uaNGlCH374oU2eB+68+uqrtjwcBEcA/qzOEqzUWUESBHQmIPNl1hl99zpbLlzdMFAnGL7du3cXTrgxd+5cOu2004KpBKVkTSDvB+owGb4Jn3jiieTauw0bNqQZM2ZQ+fLls4ZWqBcuX76cLr30Ulq4cGFyqavhw4dTt27dChUH2g0CIJBjBGQBP4L9HDMk1C14AvBlb7cAeHnjBWkQ0JUAfNmbZcDLGy9Ig4CuBODL6pYBK3VWhS754osv0iWXXCLEcMYZZyT7zYsVK5Y8f99999Gtt95qk61duzYtWLCAeOYdpHAIwJ/VuYKVOitIgoDOBGS+zDqj715ny4WrGwbq+Oe7c+dOqly5Mm3cuNFWGC9hyhNxpPM92wU4CI1AQQzUYXp8M+7YsQNrrQVwK23evJlKlSpFRYsWDaA0FAECIAAC0RCQBR0I9qPhj1pAICgC8GVvJMHLGy9Ig4CuBODL3iwDXt54QRoEdCUAX1a3DFipsyp0yV9++YWqVKlCu3fvtqEYMGAADR48mPbaa6/kS1F+OdavXz/atWtXSo4H5/DsOrVq1UrlYSd4AvBndaZgpc4KkiCgMwGZL7PO6LvX2XLh6oaBOv75vvzyy9S2bVtXQXfeeSfdfvvtrnxkRE+gYAbqRI8WNYIACIAACOhEQBbwI9jXyUrQBQQyE4AvZ2ZklQAvKw3sg0DuEoAve7MdeHnjBWkQ0JUAfFndMmClzgqSROPGjaOOHTu6UBx99NFUqVIl+vzzz+mnn36yneevsV955RVq3LixLR8HwROAP6szBSt1VpAEAZ0JyHyZdUbfvc6WC1c3DNTxz7dFixY0c+ZMW0E8KHvlypVUrVo1Wz4O4iGAgTrxcEetIAACIAACEROQBfwI9iM2BKoDAZ8E4MveAIKXN16QBgFdCcCXvVkGvLzxgjQI6EoAvqxuGbBSZwXJfwmMHDmS+vfvT9u3b8+I5LzzzqOnn36aDjzwwIyyEPBPAP6szhCs1FlBEgR0JiDzZdYZffc6Wy5c3TBQxx/fNWvWUI0aNeiff/6xFdS8eXN68803bXk4iI8ABurExx41gwAIgAAIREhAFvAj2I/QCKgKBAIgAF/2BhG8vPGCNAjoSgC+7M0y4OWNF6RBQFcC8GV1y4CVOitI7iGwfv16Gj58OD3zzDO0adOmPSf+t1evXj3q1q0bderUyXUOGeERgD+rswUrdVaQBAGdCch8mXVG373OlgtXNwzU8cd36NChxEubOtPEiROpXbt2zmwcx0QAA3ViAo9qQQAEQAAEoiUgC/gR7EdrB9QGAn4JwJe9EQQvb7wgDQK6EoAve7MMeHnjBWkQ0JUAfFndMmClzgqSYgK//vorLVu2jPjra54555BDDqGDDz5YLIzcUAnAn9XxgpU6K0iCgM4EZL7MOqPvXmfLhavbqFGjqEePHrZKjj/+eProo49seTgQE+AlTXk5U2s64IADksubFi9e3JqN/RgJYKBOjPBRNQiAAAiAQHQEZAE/gv3obICaQCAIAvBlbxTByxsvSIOArgTgy94sA17eeEEaBHQlAF9WtwxYqbOCJAjoTgD+rG4hsFJnBUkQ0JmAzJdZZ/Td62y5cHUbO3asa1a/pk2b0uzZs8OtOE9Kr1q1Kq1du9bWmptuuolGjx5ty8NBvAQwUCde/qgdBEAABEAgIgKygB/BfkQGQDUgEBAB+LI3kODljRekQUBXAvBlb5YBL2+8IA0CuhKAL6tbBqzUWUESBHQnAH9WtxBYqbOCJAjoTEDmy6wz+u51tly4ui1evJgaNWpkq6Rnz57ES2IhZSbQsmVLmj59ekqQZ9Hh2ROrVauWysNO/AQwUCd+G0ADEAABEACBCAjIAn4E+xHARxUgECAB+LI3mODljRekQUBXAvBlb5YBL2+8IA0CuhKAL6tbBqzUWUESBHQnAH9WtxBYqbOCJAjoTEDmy6wz+u51tlz4uvHSV48//jjt2LGDGjZsSDNmzKDy5cuHX3Ee1LB8+XK69NJLaeHChcSDdIYPH07dunXLg5blVxMwUCe/7InWgAAIgAAISAjIAn4E+xJgyAYBTQnAl70ZBry88YI0COhKAL7szTLg5Y0XpEFAVwLwZXXLgJU6K0iCgO4E4M/qFgIrdVaQBAGdCch8mXVG373OlotGt507d9L27dupTJky0VSYZ7Vs3ryZSpUqRUWLFs2zluVHczBQJz/siFaAAAiAAAhkICAL+BHsZwCH0yCgGQH4sjeDgJc3XpAGAV0JwJe9WQa8vPGCNAjoSgC+rG4ZsFJnBUkQ0J0A/FndQmClzgqSIKAzAZkvs87ou9fZctANBEDALwEM1PFLENeDAAiAAAjkBAFZwI9gPyfMByVBIEUAvpxCobQDXkqYIAQC2hOAL3szEXh54wVpENCVAHxZ3TJgpc4KkiCgOwH4s7qFwEqdFSRBQGcCMl9mndF3r7PloBsIgIBfAhio45cgrgcBEAABEMgJArKAH8F+TpgPSoJAigB8OYVCaQe8lDBBCAS0JwBf9mYi8PLGC9IgoCsB+LK6ZcBKnRUkQUB3AvBndQuBlTorSIKAzgRkvsw6o+9eZ8tBNxAAAb8EMFDHL0FcDwIgAAIgkBMEZAE/gv2cMB+UBIEUAfhyCoXSDngpYYIQCGhPAL7szUTg5Y0XpEFAVwLwZXXLgJU6K0iCgO4E4M/qFgIrdVaQBAGdCch8mXVG373OloNuIAACfglgoI5fgrgeBEAABEAgJwjIAn4E+zlhPigJAikC8OUUCqUd8FLCBCEQ0J4AfNmbicDLGy9Ig4CuBODL6pYBK3VWkAQB3QnAn9UtBFbqrCAJAjoTkPky64y+e50tB91AAAT8EsBAHb8EcT0IgAAIgEBOEJAF/Aj2c8J8UBIEUgTgyykUSjvgpYQJQiCgPQH4sjcTgZc3XpAGAV0JwJfVLQNW6qwgCQK6E4A/q1sIrNRZQRIEdCYg82XWGX33OlsOuoEACPglgIE6fgniehAAARAAgZwgIAv4EeznhPmgJAikCMCXUyiUdsBLCROEQEB7AvBlbyYCL2+8IA0CuhKAL6tbBqzUWUESBHQnAH9WtxBYqbOCJAjoTEDmy6wz+u51thx0AwEQ8EsAA3X8EsT1IAACIAACOUFAFvAj2M8J80FJEEgRgC+nUCjtgJcSJgiBgPYE4MveTARe3nhBGgR0JQBfVrcMWKmzgiQI6E4A/qxuIbBSZwVJENCZgMyXWWf03etsOegGAiDglwAG6vgliOtBAARAAARygoAs4EewnxPmg5IgkCIAX06hUNoBLyVMEAIB7QnAl72ZCLy88YI0COhKAL6sbhmwUmcFSRDQnQD8Wd1CYKXOCpIgoDMBmS+zzui719ly0A0EQMAvAQzU8UsQ14MACIAACOQEAVnAj2A/J8wHJUEgRQC+nEKhtANeSpggBALaE4AvezMReHnjBWkQ0JUAfFndMmClzgqSIKA7AfizuoXASp0VJEFAZwIyX2ad0Xevs+WgGwiAgF8CGKjjlyCuBwEQAAEQyAkCsoAfwX5OmA9KgkCKAHw5hUJpB7yUMEEIBLQnAF/2ZiLw8sYL0iCgKwH4srplwEqdFSRBQHcC8Gd1C4GVOitIgoDOBGS+zDqj715ny0E3EAABvwQwUMcvQVwPAiAAAiCQEwRkAT+C/ZwwH5QEgRQB+HIKhdIOeClhghAIaE8AvuzNRODljRekQUBXAvBldcuAlTorSIKA7gTgz+oWAit1VpAEAZ0JyHyZdUbfvc6Wg24gAAJ+CWCgjl+CuB4EQAAEQCAnCMgCfgT7OWE+KAkCKQLw5RQKpR3wUsIEIRDQngB82ZuJwMsbL0iDgK4E4MvqlgErdVaQBAHdCcCf1S0EVuqsIAkCOhOQ+TLrjL57nS0H3UAABPwSwEAdvwRxPQiAAAiAQE4QkAX8CPZzwnxQEgRSBODLKRRKO+ClhAlCIKA9AfiyNxOBlzdekAYBXQnAl9UtA1bqrCAJAroTgD+rWwis1FlBEgR0JiDzZdYZffc6Ww66gQAI+CWAgTp+CeJ6EAABEACBnCAgC/gR7OeE+aAkCKQIwJdTKJR2wEsJE4RAQHsC8GVvJgIvb7wgDQK6EoAvq1sGrNRZQRIEdCcAf1a3EFips4IkCOhMQObLrDP67nW2HHQDARDwSwADdfwSxPUgAAIgAAI5QUAW8CPYzwnzQUkQSBGAL6dQKO2AlxImCIGA9gTgy95MBF7eeEEaBHQlAF9WtwxYqbOCJAjoTgD+rG4hsFJnBUkQ0JmAzJdZZ/Td62w56AYCIOCXAAbq+CWI60EABEAABHKCgCzgR7CfE+aDkiCQIgBfTqFQ2gEvJUwQAgHtCcCXvZkIvLzxgjQI6EoAvqxuGbBSZwVJENCdAPxZ3UJgpc4KkiCgMwGZL7PO6LvX2XLQDQRAwC8BDNTxSxDXgwAIgAAI5AQBWcCPYD8nzAclQSBFAL6cQqG0A15KmCAEAtoTgC97MxF4eeMFaRDQlQB8Wd0yYKXOCpIgoDsB+LO6hcBKnRUkQUBnAjJfZp3Rd6+z5aAbCICAXwIYqOOXIK4HARAAARDICQKygB/Bfk6YD0qCQIoAfDmFQmkHvJQwQQgEtCcAX/ZmIvDyxgvSIKArAfiyumXASp0VJEFAdwLwZ3ULgZU6K0iCgM4EZL7MOqPvXmfLQTcQAAG/BDBQxy9BXA8CIAACIJATBGQBP4L9nDAflASBFAH4cgqF0g54KWGCEAhoTwC+7M1E4OWNF6RBQFcC8GV1y4CVOitIgoDuBODP6hYCK3VWkAQBnQnIfJl1Rt+9zpaDbiAAAn4JYKCOX4K4HgRAAARAICcIyAJ+BPs5YT4oCQIpAvDlFAqlHfBSwgQhENCeAHzZm4nAyxsvSIOArgTgy+qWASt1VpAEAd0JwJ/VLQRW6qwgCQI6E5D5MuuMvnudLQfdQAAE/BLAQB2/BHE9CIAACIBAThCQBfwI9nPCfFASBFIE4MspFEo74KWECUIgoD0B+LI3E4GXN16QBgFdCcCX1S0DVuqsIAkCuhOAP6tbCKzUWUESBHQmIPNl1hl99zpbDrqBAAj4JYCBOn4J4noQAAEQAIGcICAL+BHs54T5oCQIpAjAl1MolHbASwkThEBAewLwZW8mAi9vvCANAroSgC+rWwas1FlBEgR0JwB/VrcQWKmzgiQI6ExA5susM/rudbYcdAMBEPBLAAN1/BLE9SAAAiAAAjlBQBbwI9jPCfNBSRBIEYAvp1Ao7YCXEiYIgYD2BODL3kwEXt54QRoEdCUAX1a3DFips4IkCOhOAP6sbiGwUmcFSRDQmYDMl1ln9N3rbDnoBgIg4JcABur4JYjrQQAEQAAEcoKALOBHsJ8T5oOSIJAiAF9OoVDaAS8lTBACAe0JwJe9mQi8vPGCNAjoSgC+rG4ZsFJnBUkQ0J0A/FndQmClzgqSIKAzAZkvs87ou9fZctANBEDALwEM1PFLENeDAAiAAAjkBAFZwI9gPyfMByVBIEUAvpxCobQDXkqYIAQC2hOAL3szEXh54wVpENCVAHxZ3TJgpc4KkiCgOwH4s7qFwEqdFSRBQGcCMl9mndF3r7PloBsIgIBfAhio45cgrgcBEAABEMgJArKAH8F+TpgPSoJAigB8OYVCaQe8lDBBCAS0JwBf9mYi8PLGC9IgoCsB+LK6ZcBKnRUkQUB3AvBndQuBlTorSIKAzgRkvsw6o+9eZ8tBNxAAAb8EMFDHL0FcDwIgAAIgkBMEZAE/gv2cMB+UBIEUAfhyCoXSDngpYYIQCGhPAL7szUTg5Y0XpEFAVwLwZXXLgJU6K0iCgO4E4M/qFgIrdVaQBAGdCch8mXVG373OloNuIAACfglgoI5fgrgeBEAABEAgJwjIAn4E+zlhPigJAikC8OUUCqUd8FLCBCEQ0J4AfNmbicDLGy9Ig4CuBODL6pYBK3VWkAQB3QnAn9UtBFbqrCAJAjoTkPky64y+e50tB91AAAT8EsBAHb8EcT0IgAAIgEBOEJAF/Aj2c8J8UBIEUgTgyykUSjvgpYQJQiCgPQH4sjcTgZc3XpAGAV0JwJfVLQNW6qwgCQK6E4A/q1sIrNRZQRIEdCYg82XWGX33OlsOuoEACPglgIE6fgniehAAARAAgZwgIAv4EeznhPmgJAikCMCXUyiUdsBLCROEQEB7AvBlbyYCL2+8IA0CuhKAL6tbBqz+v107WpUchAEA+v9/vcx9kIC6pEggynkLxYo9mYROSd7KSgLdBdRzPkOs8lZWEugssKvl35l9u++cOWcjQOBUwKDOqaD7CRAgQOAKgd0Lv5f9K9LnkASGgFoeFKmAV4rJIgLtBdTytxTx+uZlNYGuAmo5nxlWeSsrCXQXUM/5DLHKW1lJoLPArpZ/Z/btvnPmnI0AgVMBgzqngu4nQIAAgSsEdi/8XvavSJ9DEhgCanlQpAJeKSaLCLQXUMvfUsTrm5fVBLoKqOV8Zljlrawk0F1APeczxCpvZSWBzgK7Wv6d2bf7zplzNgIETgUM6pwKup8AAQIErhDYvfB72b8ifQ5JYAio5UGRCnilmCwi0F5ALX9LEa9vXlYT6CqglvOZYZW3spJAdwH1nM8Qq7yVlQQ6C+xq+Xdm3+47Z87ZCBA4FTCocyrofgIECBC4QmD3wu9l/4r0OSSBIaCWB0Uq4JVisohAewG1/C1FvL55WU2gq4BazmeGVd7KSgLdBdRzPkOs8lZWEugssKvl35l9u++cOWcjQOBUwKDOqaD7CRAgQOAKgd0Lv5f9K9LnkASGgFoeFKmAV4rJIgLtBdTytxTx+uZlNYGuAmo5nxlWeSsrCXQXUM/5DLHKW1lJoLPArpZ/Z/btvnPmnI0AgVMBgzqngu4nQIAAgSsEdi/8XvavSJ9DEhgCanlQpAJeKSaLCLQXUMvfUsTrm5fVBLoKqOV8Zljlrawk0F1APeczxCpvZSWBzgK7Wv6d2bf7zplzNgIETgUM6pwKup8AAQIErhDYvfB72b8ifQ5JYAio5UGRCnilmCwi0F5ALX9LEa9vXlYT6CqglvOZYZW3spJAdwH1nM8Qq7yVlQQ6C+xq+Xdm3+47Z87ZCBA4FTCocyrofgIECBC4QmD3wu9l/4r0OSSBIaCWB0Uq4JVisohAewG1/C1FvL55WU2gq4BazmeGVd7KSgLdBdRzPkOs8lZWEugssKvl35l9u++cOWcjQOBUwKDOqaD7CRAgQOAKgd0Lv5f9K9LnkASGgFoeFKmAV4rJIgLtBdTytxTx+uZlNYGuAmo5nxlWeSsrCXQXUM/5DLHKW1lJoLPArpZ/Z/btvnPmnI0AgVMBgzqngu4nQIAAgSsEdi/8XvavSJ9DEhgCanlQpAJeKSaLCLQXUMvfUsTrm5fVBLoKqOV8Zljlrawk0F1APeczxCpvZSWBzgK7Wv6d2bf7zplzNgIETgUM6pwKup8AAQIErhDYvfB72b8ifQ5JYAio5UGRCnilmCwi0F5ALX9LEa9vXlYT6CqglvOZYZW3spJAdwH1nM8Qq7yVlQQ6C+xq+Xdm3+47Z87ZCBA4FTCocyrofgIECBC4QuB/L/xXPIBDEiDwXwF/3Nc8et/axVUCrwjofetM6n1rF1cJvCKg982Z1PdmE1cIvCag980Z1ftmE1cIvCag972WUc9DgEAUMKgTNcQECBAg8KyAP+/PptaDEfgT8Md9/UPQ+9YurhJ4RUDvW2dS71u7uErgFQG9b86kvjebuELgNQG9b86o3jebuELgNQG977WMeh4CBKKAQZ2oISZAgACBZwX8eX82tR6MwJ+AP+7rH4Let3ZxlcArAnrfOpN639rFVQKvCOh9cyb1vdnEFQKvCeh9c0b1vtnEFQKvCeh9r2XU8xAgEAUM6kQNMQECBAg8K+DP+7Op9WAE/gT8cV//EPS+tYurBF4R0PvWmdT71i6uEnhFQO+bM6nvzSauEHhNQO+bM6r3zSauEHhNQO97LaOehwCBKGBQJ2qICRAgQOBZAX/en02tByPwJ+CP+/qHoPetXVwl8IqA3rfOpN63dnGVwCsCet+cSX1vNnGFwGsCet+cUb1vNnGFwGsCet9rGfU8BAhEAYM6UUNMgAABAs8K+PP+bGo9GIE/AX/c1z8EvW/t4iqBVwT0vnUm9b61i6sEXhHQ++ZM6nuziSsEXhPQ++aM6n2ziSsEXhPQ+17LqOchQCAKGNSJGmICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECRQIGdYpgbUuAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgChjUiRpiAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAkUCBnWKYG1LgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIAoY1IkaYgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJFAgZ1imBtS4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCAKGNSJGmICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECRQIGdYpgbUuAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgChjUiRpiAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAkUCBnWKYG1LgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIAoY1IkaYgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJFAgZ1imBtS4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCAKGNSJGmICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECRQIGdYpgbUuAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgChjUiRpiAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAkUCBnWKYG1LgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIAoY1IkaYgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJFAgZ1imBtS4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCAKGNSJGmICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECRQIGdYpgbUuAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgChjUiRpiAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAkUCBnWKYG1LgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIAoY1IkaYgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJFAgZ1imBtS4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCAKGNSJGmICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECRQIGdYpgbUuAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgChjUiRpiAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAkUCBnWKYG1LgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIAoY1IkaYgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJFAgZ1imBtS4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCAKGNSJGmICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECRQIGdYpgbUuAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgChjUiRpiAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAkUCBnWKYG1LgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIAoY1IkaYgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJFAgZ1imBtS4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCAKGNSJGmICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECRQIGdYpgbUuAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgChjUiRpiAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAkUCBnWKYG1LgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIAoY1IkaYgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJFAgZ1imBtS4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCAKGNSJGmICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECRQIGdYpgbUuAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgChjUiRpiAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAkUCBnWKYG1LgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIAoY1IkaYgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJFAgZ1imBtS4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCAKGNSJGmICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQI3D59wAABTZJREFUIECAAAECRQIGdYpgbUuAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgChjUiRpiAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAkUCBnWKYG1LgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIAoY1IkaYgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJFAgZ1imBtS4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCAKGNSJGmICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECRQIGdYpgbUuAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgChjUiRpiAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAkUCBnWKYG1LgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIAoY1IkaYgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJFAgZ1imBtS4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCAKGNSJGmICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECRQIGdYpgbUuAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgChjUiRpiAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAkUCBnWKYG1LgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIAoY1IkaYgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJFAgZ1imBtS4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCAKGNSJGmICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECRQIGdYpgbUuAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgChjUiRpiAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAkUCBnWKYG1LgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIAoY1IkaYgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJFAgZ1imBtS4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCAKGNSJGmICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECRQIGdYpgbUuAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgChjUiRpiAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAkUCBnWKYG1LgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIAoY1IkaYgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJFAgZ1imBtS4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCAKGNSJGmICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECRQL/AD3x3Nmbl+EbAAAAAElFTkSuQmCC"
    }
   },
   "cell_type": "markdown",
   "id": "914a77bf-57de-4b34-bf6c-cda9d35a78ea",
   "metadata": {
    "tags": []
   },
   "source": [
    "On the first part, we assume we know how to implement the dual of $f$, and get $s$ according to the algorithm in [[1](#first)]:![Screen Shot 2023-06-27 at 18.05.48.png](attachment:663333d5-eb52-4150-a00d-8683e816d860.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8ede4222-6164-4c18-8679-bc93d9071b21",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:46:22.178388Z",
     "iopub.status.busy": "2024-05-07T14:46:22.178141Z",
     "iopub.status.idle": "2024-05-07T14:46:29.805101Z",
     "shell.execute_reply": "2024-05-07T14:46:29.804393Z"
    }
   },
   "outputs": [],
   "source": [
    "from classiq import (\n",
    "    Constraints,\n",
    "    Output,\n",
    "    QArray,\n",
    "    QBit,\n",
    "    QCallable,\n",
    "    QNum,\n",
    "    allocate,\n",
    "    bind,\n",
    "    create_model,\n",
    "    execute,\n",
    "    hadamard_transform,\n",
    "    invert,\n",
    "    phase_oracle,\n",
    "    qfunc,\n",
    "    show,\n",
    "    synthesize,\n",
    ")\n",
    "\n",
    "\n",
    "@qfunc\n",
    "def hidden_shift(\n",
    "    oracle: QCallable[QArray[QBit]],\n",
    "    oracle_shifted: QCallable[QArray[QBit]],\n",
    "    target: QArray[QBit],\n",
    ") -> None:\n",
    "    hadamard_transform(target)\n",
    "    oracle_shifted(target)\n",
    "    hadamard_transform(target)\n",
    "    oracle(target)\n",
    "    hadamard_transform(target)\n",
    "\n",
    "\n",
    "NUM_VARIABLES = 4\n",
    "\n",
    "\n",
    "@qfunc\n",
    "def main(s: Output[QArray[QBit]]) -> None:\n",
    "\n",
    "    @qfunc\n",
    "    def arith_func(vars: QArray[QBit, NUM_VARIABLES], res: QBit):\n",
    "        a, b, c, d = QBit(\"a\"), QBit(\"b\"), QBit(\"c\"), QBit(\"d\")\n",
    "        bind(vars, [a, b, c, d])\n",
    "        res ^= (a & b) ^ (c & d) == 1\n",
    "        bind([a, b, c, d], vars)\n",
    "\n",
    "    @qfunc\n",
    "    def arith_func_shifted(vars: QArray[QBit, NUM_VARIABLES], res: QBit):\n",
    "        a, b, c, d = QBit(\"a\"), QBit(\"b\"), QBit(\"c\"), QBit(\"d\")\n",
    "        bind(vars, [a, b, c, d])\n",
    "        res ^= ((a ^ 1) & b) ^ (c & d) == 1\n",
    "        bind([a, b, c, d], vars)\n",
    "\n",
    "    allocate(NUM_VARIABLES, s)\n",
    "\n",
    "    hidden_shift(\n",
    "        lambda y: phase_oracle(lambda vars, result: arith_func(vars, result), y),\n",
    "        lambda y: phase_oracle(\n",
    "            lambda vars, result: arith_func_shifted(vars, result), y\n",
    "        ),\n",
    "        s,\n",
    "    )\n",
    "\n",
    "\n",
    "constraints = Constraints(optimization_parameter=\"width\")\n",
    "qmod = create_model(main, constraints)\n",
    "qprog = synthesize(qmod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8c12f8f6-025f-43f5-b5a5-821b1a06640d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:46:29.810320Z",
     "iopub.status.busy": "2024-05-07T14:46:29.808922Z",
     "iopub.status.idle": "2024-05-07T14:46:29.827350Z",
     "shell.execute_reply": "2024-05-07T14:46:29.826626Z"
    }
   },
   "outputs": [],
   "source": [
    "from classiq import write_qmod\n",
    "\n",
    "write_qmod(qmod, \"hidden_shift_simple\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5a2594a0-80b5-4ede-9b07-edf8ed811453",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:46:29.832392Z",
     "iopub.status.busy": "2024-05-07T14:46:29.831045Z",
     "iopub.status.idle": "2024-05-07T14:46:32.115352Z",
     "shell.execute_reply": "2024-05-07T14:46:32.114637Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opening: https://platform.classiq.io/circuit/d31a7cae-c023-4371-8c3b-111808fe6302?version=0.41.0.dev39%2B79c8fd0855\n"
     ]
    }
   ],
   "source": [
    "from classiq import show\n",
    "\n",
    "qprog = synthesize(qmod)\n",
    "show(qprog)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "168660d6-9ab4-4429-a5c7-6bc8e23bda2a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:46:32.118168Z",
     "iopub.status.busy": "2024-05-07T14:46:32.117844Z",
     "iopub.status.idle": "2024-05-07T14:46:34.585601Z",
     "shell.execute_reply": "2024-05-07T14:46:34.584825Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'1000': 1000}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from classiq.execution import ExecutionDetails\n",
    "\n",
    "res = execute(qprog).result()\n",
    "sample_results = res[0].value\n",
    "sample_results.counts_of_output(\"s\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "64d54218-7d9c-420a-92ff-1f719d2aa638",
   "metadata": {},
   "source": [
    "# More complex functions"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "55139935-68d5-4b8b-83dc-e00345c85ef4",
   "metadata": {},
   "source": [
    "We take a Maiorana-McFarland function with random permutation on the `y` and `h` function is the `and` operation between all the y-variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7e75d67c-7908-4f80-afdb-a82ec7ff34bc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:46:34.588381Z",
     "iopub.status.busy": "2024-05-07T14:46:34.587841Z",
     "iopub.status.idle": "2024-05-07T14:46:34.601364Z",
     "shell.execute_reply": "2024-05-07T14:46:34.600704Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import random\n",
    "from functools import reduce\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "NUM_VARIABLES = 16\n",
    "\n",
    "# Define the list\n",
    "my_list = list(range(NUM_VARIABLES // 2))\n",
    "\n",
    "# Get a random permutation\n",
    "random.seed(1)\n",
    "random.shuffle(my_list)\n",
    "\n",
    "# Create a permutation dict and its inverse\n",
    "perm_dict = {i: my_list[i] for i in range(NUM_VARIABLES // 2)}\n",
    "inverse_perm_dict = {v: k for k, v in perm_dict.items()}\n",
    "\n",
    "\n",
    "def h(y):\n",
    "    return reduce(lambda a, b: a & b, [y[i] for i in range(NUM_VARIABLES // 2)])\n",
    "\n",
    "\n",
    "def h_dual(x):\n",
    "    return reduce(\n",
    "        lambda a, b: a & b, [x[inverse_perm_dict[i]] for i in range(NUM_VARIABLES // 2)]\n",
    "    )\n",
    "\n",
    "\n",
    "def f_func(x, y):\n",
    "    return (\n",
    "        reduce(\n",
    "            lambda a, b: a ^ b,\n",
    "            [x[i] & y[perm_dict[i]] for i in range(NUM_VARIABLES // 2)],\n",
    "        )\n",
    "    ) ^ h(y)\n",
    "\n",
    "\n",
    "def f_dual_func(x, y):\n",
    "    return (\n",
    "        reduce(\n",
    "            lambda a, b: a ^ b,\n",
    "            [x[inverse_perm_dict[i]] & y[i] for i in range(NUM_VARIABLES // 2)],\n",
    "        )\n",
    "    ) ^ h_dual(x)\n",
    "\n",
    "\n",
    "def shifted(x, y, bits):\n",
    "    x = x.copy()\n",
    "    y = y.copy()\n",
    "    for bit in bits:\n",
    "        if bit < NUM_VARIABLES >> 2:\n",
    "            x[bit] = x[bit] ^ 1\n",
    "        else:\n",
    "            bit = bit - NUM_VARIABLES // 2\n",
    "            y[bit] = y[bit] ^ 1\n",
    "    return f_func(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "69f56fed-0934-4365-9a3c-d4bbf9c62cdc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:46:34.603610Z",
     "iopub.status.busy": "2024-05-07T14:46:34.603423Z",
     "iopub.status.idle": "2024-05-07T14:46:34.606539Z",
     "shell.execute_reply": "2024-05-07T14:46:34.605939Z"
    }
   },
   "outputs": [],
   "source": [
    "shifted_bits = [1, 3, 9]\n",
    "g_func = lambda x, y: shifted(x, y, shifted_bits)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c27a578d-5380-460d-9833-15557d4e292a",
   "metadata": {},
   "source": [
    "## Now create the ciruit:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b05db048-d8c7-4eda-9592-61f7b5275fff",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:46:34.609084Z",
     "iopub.status.busy": "2024-05-07T14:46:34.608599Z",
     "iopub.status.idle": "2024-05-07T14:46:34.636926Z",
     "shell.execute_reply": "2024-05-07T14:46:34.636292Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "f_dual: (((((((((x6) & (x9)) ^ ((x3) & (x10))) ^ ((x8) & (x11))) ^ ((x1) & (x12))) ^ ((x7) & (x13))) ^ ((x4) & (x14))) ^ ((x2) & (x15))) ^ ((x5) & (x16))) ^ ((((((((x6) & (x3)) & (x8)) & (x1)) & (x7)) & (x4)) & (x2)) & (x5))\n",
      "g: (((((((((x1) & (x12)) ^ (((x2) ^ 1) & (x15))) ^ ((x3) & ((x10) ^ 1))) ^ (((x4) ^ 1) & (x14))) ^ ((x5) & (x16))) ^ ((x6) & (x9))) ^ ((x7) & (x13))) ^ ((x8) & (x11))) ^ ((((((((x9) & ((x10) ^ 1)) & (x11)) & (x12)) & (x13)) & (x14)) & (x15)) & (x16))\n"
     ]
    }
   ],
   "source": [
    "@qfunc\n",
    "def g_qfunc(vars: QArray[QBit, NUM_VARIABLES], res: QBit):\n",
    "    qubit_vars = [QBit(f\"x{i+1}\") for i in range(NUM_VARIABLES)]\n",
    "    bind(vars, qubit_vars)\n",
    "    x = qubit_vars[: NUM_VARIABLES // 2]\n",
    "    y = qubit_vars[NUM_VARIABLES // 2 :]\n",
    "    print(\"g:\", g_func(x, y))\n",
    "    res ^= (g_func(x, y)) == 1\n",
    "    bind(qubit_vars, vars)\n",
    "\n",
    "\n",
    "@qfunc\n",
    "def f_dual_qfunc(vars: QArray[QBit, NUM_VARIABLES], res: QBit):\n",
    "    qubit_vars = [QBit(f\"x{i+1}\") for i in range(NUM_VARIABLES)]\n",
    "    bind(vars, qubit_vars)\n",
    "    x = qubit_vars[: NUM_VARIABLES // 2]\n",
    "    y = qubit_vars[NUM_VARIABLES // 2 :]\n",
    "    print(\"f_dual:\", f_dual_func(x, y))\n",
    "    res ^= (f_dual_func(x, y)) == 1\n",
    "    bind(qubit_vars, vars)\n",
    "\n",
    "\n",
    "@qfunc\n",
    "def f_qfunc(vars: QArray[QBit, NUM_VARIABLES], res: QBit):\n",
    "    qubit_vars = [QBit(f\"x{i+1}\") for i in range(NUM_VARIABLES)]\n",
    "    bind(vars, qubit_vars)\n",
    "    x = qubit_vars[: NUM_VARIABLES // 2]\n",
    "    y = qubit_vars[NUM_VARIABLES // 2 :]\n",
    "    print(\"f:\", f_func(x, y))\n",
    "    res ^= (f_func(x, y)) == 1\n",
    "    bind(qubit_vars, vars)\n",
    "\n",
    "\n",
    "@qfunc\n",
    "def main(s: Output[QArray[QBit]]) -> None:\n",
    "    allocate(NUM_VARIABLES, s)\n",
    "\n",
    "    hidden_shift(\n",
    "        lambda y: phase_oracle(lambda vars, result: f_dual_qfunc(vars, result), y),\n",
    "        lambda y: phase_oracle(lambda vars, result: g_qfunc(vars, result), y),\n",
    "        s,\n",
    "    )\n",
    "\n",
    "\n",
    "constraints = Constraints(optimization_parameter=\"width\")\n",
    "qmod = create_model(main, constraints=constraints)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7523b1ea-4de9-4470-9a52-7d177ca7bdc0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:46:34.639447Z",
     "iopub.status.busy": "2024-05-07T14:46:34.639076Z",
     "iopub.status.idle": "2024-05-07T14:46:34.652733Z",
     "shell.execute_reply": "2024-05-07T14:46:34.652092Z"
    }
   },
   "outputs": [],
   "source": [
    "write_qmod(qmod, \"hidden_shift_complex\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "adc3681d-079c-4d69-bd72-9d54dd6972e0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:46:34.655261Z",
     "iopub.status.busy": "2024-05-07T14:46:34.654815Z",
     "iopub.status.idle": "2024-05-07T14:47:16.373908Z",
     "shell.execute_reply": "2024-05-07T14:47:16.373226Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opening: https://platform.classiq.io/circuit/fb944da8-cb3b-4630-880b-413335d266d7?version=0.41.0.dev39%2B79c8fd0855\n"
     ]
    }
   ],
   "source": [
    "qprog = synthesize(qmod)\n",
    "show(qprog)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "12a84249-1023-4d77-bf3f-f168426bc393",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:47:16.376583Z",
     "iopub.status.busy": "2024-05-07T14:47:16.376057Z",
     "iopub.status.idle": "2024-05-07T14:47:30.042330Z",
     "shell.execute_reply": "2024-05-07T14:47:30.041635Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'0101000001000000': 1000}"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from classiq.execution import ExecutionDetails\n",
    "\n",
    "res = execute(qprog).result()\n",
    "sample_results = res[0].value\n",
    "sample_results.counts_of_output(\"s\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "559ee1f5-b811-42a0-aaa5-e28ab40df5d6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:47:30.044761Z",
     "iopub.status.busy": "2024-05-07T14:47:30.044303Z",
     "iopub.status.idle": "2024-05-07T14:47:30.047807Z",
     "shell.execute_reply": "2024-05-07T14:47:30.047202Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "expected_s = \"\".join(\"1\" if i in shifted_bits else \"0\" for i in range(NUM_VARIABLES))\n",
    "assert list(sample_results.counts_of_output(\"s\").keys())[0] == expected_s"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a4e1504-078d-4fa5-ab3d-29a8b4ac8714",
   "metadata": {},
   "source": [
    "And indeed we got the correct shift!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c698b65-fb3d-4c7e-968e-83b77b83cd48",
   "metadata": {
    "tags": []
   },
   "source": [
    "# Hidden Shift without the dual function"
   ]
  },
  {
   "attachments": {
    "e8a93a2f-8965-4181-9083-78e12dc0f48b.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "0bf70e08-3ea7-43b8-afc2-0271f124323f",
   "metadata": {},
   "source": [
    "We now use the second algorithm described in [[2](#second)]. This algorithm only requires to implement $f$ and not its dual, however requires $O(n)$ samples from the circuit.\n",
    "![Screen Shot 2023-06-27 at 18.08.23.png](attachment:e8a93a2f-8965-4181-9083-78e12dc0f48b.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b5422ed1-23d9-48cf-bbbe-429344a32b97",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:47:30.050525Z",
     "iopub.status.busy": "2024-05-07T14:47:30.050018Z",
     "iopub.status.idle": "2024-05-07T14:47:30.083282Z",
     "shell.execute_reply": "2024-05-07T14:47:30.082583Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "f: (((((((((x1) & (x12)) ^ ((x2) & (x15))) ^ ((x3) & (x10))) ^ ((x4) & (x14))) ^ ((x5) & (x16))) ^ ((x6) & (x9))) ^ ((x7) & (x13))) ^ ((x8) & (x11))) ^ ((((((((x9) & (x10)) & (x11)) & (x12)) & (x13)) & (x14)) & (x15)) & (x16))\n",
      "g: (((((((((x1) & (x12)) ^ (((x2) ^ 1) & (x15))) ^ ((x3) & ((x10) ^ 1))) ^ (((x4) ^ 1) & (x14))) ^ ((x5) & (x16))) ^ ((x6) & (x9))) ^ ((x7) & (x13))) ^ ((x8) & (x11))) ^ ((((((((x9) & ((x10) ^ 1)) & (x11)) & (x12)) & (x13)) & (x14)) & (x15)) & (x16))\n"
     ]
    }
   ],
   "source": [
    "from classiq import Z\n",
    "\n",
    "\n",
    "@qfunc\n",
    "def hidden_shift_no_dual(\n",
    "    oracle: QCallable[QArray[QBit], QBit],\n",
    "    oracle_shifted: QCallable[QArray[QBit], QBit],\n",
    "    target: QArray[QBit],\n",
    "    ind: QBit,\n",
    ") -> None:\n",
    "    hadamard_transform(target)\n",
    "    oracle(target, ind)\n",
    "    Z(ind)\n",
    "    oracle_shifted(target, ind)\n",
    "    hadamard_transform(target)\n",
    "\n",
    "\n",
    "NUM_VARIABLES = 16\n",
    "\n",
    "\n",
    "@qfunc\n",
    "def main(target: Output[QArray[QBit]], ind: Output[QBit]) -> None:\n",
    "\n",
    "    allocate(NUM_VARIABLES, target)\n",
    "    allocate(1, ind)\n",
    "\n",
    "    hidden_shift_no_dual(\n",
    "        lambda vars, result: f_qfunc(vars, result),\n",
    "        lambda vars, result: g_qfunc(vars, result),\n",
    "        target,\n",
    "        ind,\n",
    "    )\n",
    "\n",
    "\n",
    "constraints = Constraints(optimization_parameter=\"width\")\n",
    "qmod = create_model(main, constraints)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e088bf1e-63d7-4d74-8f68-5aa5b770dd9c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:47:30.085697Z",
     "iopub.status.busy": "2024-05-07T14:47:30.085404Z",
     "iopub.status.idle": "2024-05-07T14:47:30.099742Z",
     "shell.execute_reply": "2024-05-07T14:47:30.099118Z"
    }
   },
   "outputs": [],
   "source": [
    "write_qmod(qmod, \"hidden_shift_no_dual\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "fecaaf9c-f314-4f93-ad34-7593c43c1cde",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:47:30.102256Z",
     "iopub.status.busy": "2024-05-07T14:47:30.101863Z",
     "iopub.status.idle": "2024-05-07T14:47:39.215410Z",
     "shell.execute_reply": "2024-05-07T14:47:39.214592Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opening: https://platform.classiq.io/circuit/04a66e6d-2062-4560-96eb-833b34502fcb?version=0.41.0.dev39%2B79c8fd0855\n"
     ]
    }
   ],
   "source": [
    "qprog = synthesize(qmod)\n",
    "show(qprog)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a63d78f6-733c-4dc5-a832-7a7cb5995e8d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:47:39.219206Z",
     "iopub.status.busy": "2024-05-07T14:47:39.218937Z",
     "iopub.status.idle": "2024-05-07T14:47:53.137968Z",
     "shell.execute_reply": "2024-05-07T14:47:53.137326Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from classiq.execution import ExecutionDetails\n",
    "\n",
    "res = execute(qprog).result()\n",
    "sample_results = res[0].value"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b8fa9c56-ea4e-41ca-bcf0-4cad795718dc",
   "metadata": {},
   "source": [
    "Out of the sampled results, we look for $n$ independent samples, from which we can extract s.\n",
    "1000 samples should be enough with a very high probability."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "0672c61d-b5bc-4669-8dcc-fb4d1433f674",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:47:53.142508Z",
     "iopub.status.busy": "2024-05-07T14:47:53.141413Z",
     "iopub.status.idle": "2024-05-07T14:47:59.534826Z",
     "shell.execute_reply": "2024-05-07T14:47:59.534190Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# The galois library is a package that extends NumPy arrays to operate over finite fields.\n",
    "# we wlll use it as our equations are binary equations\n",
    "import galois\n",
    "\n",
    "# here we work over boolean arithmetics - F(2)\n",
    "GF = galois.GF(2)\n",
    "\n",
    "\n",
    "def is_independent_set(vectors):\n",
    "    matrix = GF(vectors)\n",
    "    rank = np.linalg.matrix_rank(matrix)\n",
    "    if rank == len(vectors):\n",
    "        return True\n",
    "    else:\n",
    "        return False\n",
    "\n",
    "\n",
    "samples = [\n",
    "    ([int(i) for i in u], int(b))\n",
    "    for u, b in sample_results.counts_of_multiple_outputs([\"target\", \"ind\"]).keys()\n",
    "]\n",
    "\n",
    "ind_v = []\n",
    "ind_b = []\n",
    "for v, b in samples:\n",
    "    if is_independent_set(ind_v + [v]):\n",
    "        ind_v.append(v)\n",
    "        ind_b.append(b)\n",
    "        if len(ind_v) == len(v):\n",
    "            # reached max set\n",
    "            break\n",
    "\n",
    "assert len(ind_v) == len(v)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c058a569-2977-445c-b70b-d8d8e6c0914a",
   "metadata": {
    "tags": []
   },
   "source": [
    "We now left with solving the equation and extracting $s$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "807ccce8-44ea-4c12-a7b8-d9c9867ab1f3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:47:59.537792Z",
     "iopub.status.busy": "2024-05-07T14:47:59.537340Z",
     "iopub.status.idle": "2024-05-07T14:47:59.547245Z",
     "shell.execute_reply": "2024-05-07T14:47:59.546627Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GF([0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0], order=2)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = np.array(ind_v)\n",
    "b = np.array(ind_b)\n",
    "\n",
    "# Solve the linear system\n",
    "s = np.linalg.solve(GF(A), GF(b))\n",
    "s"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e47bb31-04e8-4698-b42e-13ca9722018e",
   "metadata": {},
   "source": [
    "And we got successfully the same shift."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d6e45751-4ce4-41ea-be38-970435250984",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-07T14:47:59.549409Z",
     "iopub.status.busy": "2024-05-07T14:47:59.549233Z",
     "iopub.status.idle": "2024-05-07T14:47:59.553107Z",
     "shell.execute_reply": "2024-05-07T14:47:59.552502Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "assert \"\".join(str(i) for i in s) == expected_s"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9c3a8e1-12a0-4dae-85d1-b3e28765ec45",
   "metadata": {
    "tags": []
   },
   "source": [
    "## References\n",
    "\n",
    "<a id='first'>[1]</a>: [Quantum algorithms for highly non-linear Boolean functions](https://arxiv.org/abs/0811.3208)\n",
    "\n",
    "<a id='second'>[2]</a>: [Quantum algorithm for the Boolean hidden shift problem](https://arxiv.org/abs/1103.3017)\n"
   ]
  }
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